About the role

Why this role is exciting

Why you'll love it here:

• 💰 Competitive Compensation. For this role our salary is targeted at $105-$140k USD per year. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. 
• 🏆  Syndio Equity. So you can share in Syndio’s success.
• 🏝  Flexible Vacation Policy. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, parental leave, and voting leave. 
• 🩺  Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents.
• 🏥  Life Insurance & Disability. Syndio covers the full premium.
• 🏦 401(k). To help you save for your future
• 📍 Remote-first in the following approved U.S. states: AZ, CA, CO, CT, DC, FL, GA, ID, IL, IA, MD, MA, MN, NE, NJ, NY, OH, OR, PA, RI, SC, SD, TX, UT, VT, VA, WA, and WI #LI-Remote

Role Progression:

In the 1st Month:

• Complete onboarding on the Syndio platform and the "Decision Intelligence" vision.
• Master the new Integration Platform and current data loading artifacts.
• Shadow 2-3 strategic client implementations and identify potential automation opportunities.
• Contribute to a pilot migration of an existing client’s data into the new platform.

At 3 Months:

• Independently lead technical implementations for new clients.
• Execute data migrations for a segment of the existing client base into the new Integration platform.
• Build reusable "Implementation Artifacts" (scripts, prompts, templates) that reduce time-to-value for the whole team.
• Contribute to the design of our new Platform’s Implementation process, identifying automation and other artifacts to minimize the client’s time to value.

By 6 Months:

• Manage a portfolio of high-complexity implementations for Syndio’s most strategic accounts utilizing automation and other artifacts to maximize client’s value in minimum time.
• Help achieve the goal of migrating 70% of the client base to the new Integration platform solution.
• Serve as a subject matter expert for "Process Embedding," ensuring clients are fully adopting the platform’s advanced setup features.

The interview overview

Below you'll find an outline of the interview plan for our Forward Deployed Engineer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min phone call with a member of our Talent Team.
2. 45-60 min Zoom deep dive with the Hiring Manager (Director of Forward Deployed Engineering).
3. 75 min hands-on technical interview with a Senior Engineer.
4. 2-3 video interviews with key members of the Customer Success and Product teams.
5. 30 min interview with the SVP of Engineering - Data Strategy.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

As a Senior/Lead Forward Deployed Engineer (SFDE) at Parloa, you’ll be on the front lines of enterprise AI adoption - delivering cutting-edge technology into some of the most complex environments in the world. Your mission: lead end-to-end deployment projects from an engineering perspective - not just implementing what exists, but engineering what’s required to make it succeed at enterprise scale.

FDEs are our in-field product engineers. You will build what doesn’t yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first - you’ll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes.

This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale

Areas of ownership:

• Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa’s deployments inside large, complex enterprise environments
• Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security
• Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements
• Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery
• Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes
• Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers
• Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility
• Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success.
• Shape the product: Act as the feedback loop between the field and our core engineering teams - turning deployment learnings into platform evolution
• Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value

Our Technology Stack: Python,TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:

• 7+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact
• Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments
• Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems
• Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems
• A builder’s mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world
• Degree in Computer Science, Engineering, or related technical field
• Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration)

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges include OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

About the Role

The New York Times is hiring a Software Engineer to join the New A.I. Products & Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations.

We're looking for a prototyper: someone who moves fast, ships real things, and has a genuine instinct for what makes a product feel good. You'll work at the intersection of applied A.I. and consumer product. You'll turn emerging capabilities — language models, content embeddings, semantic search — into features that help Times readers discover, understand, and engage more deeply with our content. You'll be working inside an organization with a strong culture of editorial judgment and independence.

You need a track record of shipping, a strong command of the modern web stack, and real hands-on time building with LLMs in production.

This is a hybrid role based in our New York City headquarters, reporting to the VP of Engineering, New AI Products and Platforms. You can typically expect to come into the office 2+ days per week.

Responsibilities:

• Prototype, iterate, and ship LLM- and embedding-powered reader experiences from early concept through production, in conjunction with other engineers and cross-functional peers
• Build across the full stack: Node.js/TypeScript backends, React frontends, and A.I. integrations connecting them
• Build net-new A.I. features and integrate them into existing Times systems and APIs — knowing when to build from scratch and when to wire things together cleanly
• Write, test, and refine prompts and retrieval pipelines; treat prompt engineering as a first-class engineering discipline
• Instrument your features with evaluations, engagement signals, and performance monitoring, and use them to make things better
• Work closely with product managers, designers, journalists, and senior engineers to translate editorial goals into working product
• Contribute to shared practices around evaluation, responsible A.I. use, and what "good" looks like inside an organization where judgment and independence are taken seriously
• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of software engineering experience with demonstrated ability to ship consumer-facing features
• Hands-on experience building with Large Language Models in a real product context — not just side projects
• Full-stack fundamentals: Node.js or TypeScript on the backend, React on the front end
• Experience navigating codebases and working within established backend infrastructure
• Proficiency in GenAI‑assisted developer tooling (e.g., Cursor, Copilot, or Claude Code) and passion for improving software delivery by leveraging these tools

Additional Qualifications:

• Experience working across both greenfield product development and integration with legacy or third-party systems
• Additional backend experience in Python, particularly for data pipelines or model integrations
• Experience with semantic search, embedding-based retrieval, or personalization systems
• Experience building agentic software — systems where models plan, take actions, or operate across multiple steps; complexity matters more than tenure
• Familiarity with evaluation frameworks or A/B testing for A.I. features
• Background in product environments where editorial or institutional judgment shapes what you ship

#LI-Hybrid

REQ-019883

About the Team

The Developer Platforms organization provides cloud infrastructure and tooling to 100+ teams and 750+ engineers in NYT Product Engineering through an internal developer platform. The DevEx Platforms team (6 engineers) focuses on developer experience and workflow automation.

We’re now expanding into more AI-assisted developer workflows using tools like Claude Code, Cursor, and Copilot to support debugging, migrations, test generation, and everyday development in a safe, measurable way.

This role sits in Developer Platforms and reports to the Engineering Manager of the DevEx Platforms team.

About the Role

As a Senior Software Engineer on DevEx Platforms, you’ll build GenAI-augmented developer experiences and platform capabilities used across all of The New York Times.

Your work will help teams ship faster and more safely, pay down technical debt through structured migrations and platform modernization, and turn effective internal practices into reusable tools and agents.

What You’ll Do

• Design and build GenAI-powered developer tooling: prompts, IDE integrations, Cursor/Claude rules, and telemetry to understand how they’re used.
• Build and run the GenAI developer platform: Tools, services, and integrations leveraging LiteLLM to power both local and background/long-running agents, providing auth, configuration, and LLM routing.
• Own guardrails and observability for agentic workflows: integrate with Datadog, DX, and FinOut, define sensible standards, and make sure agents interact with Jira, GitHub, and internal platforms in a safe, auditable way.
• Work closely with engineers and managers across Product Engineering to understand how they build software today and to design solutions that actually fit the way they work.
• Support our mission and values, including journalistic independence, and keep ethics and safety central to how we use AI in developer workflows.
• This role includes limited on-call responsibilities; the schedule will be set when you join.Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.
• You will report to the Engineering Manager of the DevEx Platforms team

Basic Qualifications:

• 5+ years of professional software engineering experience
• 2+ years of experience improving developer experience through workflows, documentation, and capabilities of the internal platform.
• Experience designing and building cloud native applications using Golang
• Hands-on experience building software using GenAI tools, like GitHub's Copilot, Cursor or Claude Code.

Preferred Qualifications:

#LI-Hybrid

REQ-018699

About the Role, Mission or Department Overview

The New AI Products and Platforms mission is a central hub for new, high-ambition AI opportunities and services at The Times. We are hiring a Senior Software Engineer to help build the backend services and infrastructure that will form our internal AI Platform.

This platform will enable teams across the company to build, deploy, and manage applications that use large language models (LLMs) to advance our journalism and our business. You will report to the Director of AI Platforms and work with a team of engineers, designers, product and project managers, data scientists, and newsroom stakeholders to make investments in AI possible across The Times.

This is a hybrid position based in our New York City headquarters. You can typically expect to come into the office two days per week.

Responsibilities:

• Design, build, and maintain scalable and reliable backend services and APIs for a central platform used by teams building AI applications across our journalism and our business.

• Take ownership of core platform components and integrations, including systems for prompt and workflow management, evaluation and tracing, and monitoring for cost, usage, and performance.

• Build and operate vector database and retrieval infrastructure to support search and AI-powered discovery experiences.

• Design and develop retrieval-augmented generation (RAG) pipelines and agentic workflows that connect our content, data, and AI models.

• Build orchestration layers for multi-step AI workflows, managing the coordination of LLM calls, retrieval, and business logic.

• Develop the infrastructure that enables teams to create and manage their AI applications, complete with metadata, observability, and access controls.

• Architect and implement data pipelines and storage solutions to support our AI systems.

• Write high-quality, maintainable, and well-tested code, primarily in backend languages like Python or Go.

• Ensure a high degree of code quality, security, and system observability.

• Collaborate with editorial, product, ML, and data teams to translate requirements into platform capabilities.

• Review code written by other software engineers on the team and provide feedback.

• Contribute to and advocate for robust testing strategies to ensure service reliability.

• Be a mentor to other software engineers to enable their growth.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 5+ years of software engineering experience, with a strong focus on backend development.

• 5+ years of experience in one or more backend programming languages such as Python or Go.

• 5+ years of experience designing, building, and operating distributed systems and APIs at scale.

• 1+ years of experience building applications with Large Language Models (LLMs) and familiarity with the surrounding ecosystem (e.g., orchestration, retrieval-augmented generation).

Preferred Qualifications:

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-019837

AI Software Engineer

The Team + The Role

Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents.

As an AI Software Engineer, you will build applied AI systems that move from prototype to production. You will bring deep technical capability, strong product judgment, and clear communication to decisions across prompting, fine-tuning, RAG, MLOps, and full-stack product delivery. You will partner closely with product and design to frame the right problems and ship AI-native experiences that hold up for real users.

This role is based in our New York office.

What this looks like day-to-day

• Applied AI systems: Design and build AI-native product experiences, including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure systems are reliable enough for real users.
• Technical decision-making: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach. You will explain those tradeoffs clearly to engineers and non-engineers.
• Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying failure modes early. You will catch hallucinations, measure quality, and implement guardrails that hold up under real-world load.
• MLOps ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems operate effectively in live production environments.
• Full-stack product delivery: Contribute across the stack when needed because the team ships products, not just models. You will help get complete user-facing AI experiences into customers’ hands.
• Product partnership: Partner closely with product and design to frame problems before implementation begins. You will push back when the framing is wrong and help the team focus on what should be built, not only how to build it.
• Research and tooling awareness: Stay current on the research and tooling landscape, including transformers, diffusion architectures, orchestration frameworks, and emerging agent patterns. You will bring relevant advances back to the team and apply them thoughtfully.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great AI Software Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• Deep hands-on experience building and shipping LLM-powered systems, including retrieval-augmented generation, tool use, and agent orchestration frameworks.
• Demonstrated ability to apply established AI engineering patterns to well-scoped problems and ship them reliably in production.
• End-to-end ownership of features from design through deployment and monitoring within a defined problem space.
• Strong command of model evaluation, including designing evaluation suites, reasoning about overfitting and bias-variance tradeoffs, and systematically detecting and mitigating hallucinations.
• Solid understanding of modern model architectures, including transformers and diffusion models, with the ability to make informed decisions about when and how to apply them.
• Production MLOps experience, including model deployment, monitoring pipelines, and latency, cost, and reliability optimization in a live environment.
• Strong full-stack fundamentals and comfort working across backend and frontend systems to ship complete user-facing AI products.
• Exceptional communication skills, with the ability to explain complex technical decisions clearly to engineers, product managers, and executives.
• Demonstrated product thinking, including the judgment to ask whether something should be built before deciding how to build it.

Nice-to-haves

• Experience fine-tuning foundation models and a clear point of view on when fine-tuning outperforms prompting approaches.
• Familiarity with AI safety considerations, guardrail frameworks, and responsible deployment practices.
• Experience building agentic or multi-step reasoning systems using tools such as LangChain, LlamaIndex, or custom orchestration frameworks.
• Background in a SaaS or product analytics environment where user behavior data informs AI design.
• Prior experience contributing to or launching a net-new team or product area.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in New York, NY is $178,000 - $195,000.

Benefits: Highly competitive, employer-heavy coverage including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Sr. AI Software Engineer

The Team + The Role

Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents.

As a Sr. AI Software Engineer, you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike.

This role is based in our New York office.

What this looks like day-to-day

• Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments.
• Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality.
• Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement guardrails that can withstand real-world load and production use.
• MLOps ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will help ensure AI systems are observable, efficient, and dependable in production.
• Full-stack product shipping: Contribute across the stack when needed because this team ships products, not just models. You will work across backend and frontend to get AI-powered experiences in front of users.
• Product partnership: Partner closely with product and design to frame problems well before writing code. You will push back when the framing is wrong and help the team focus on what should be built, not just what can be built.
• Research and tooling awareness: Stay current on the research and tooling landscape, including transformers, diffusion architectures, orchestration frameworks, and emerging agent patterns. You will bring relevant advances back to the team and apply them thoughtfully.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Sr. AI Software Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• Deep hands-on experience building and shipping LLM-powered systems, including retrieval-augmented generation, tool use, and agent orchestration frameworks.
• Strong technical depth in system design, including choosing the right architecture, identifying failure modes early, and making tradeoffs that hold up across the product lifecycle.
• Experience owning technical quality beyond your own features, including setting standards, catching problems in review, and improving shared infrastructure and tooling.
• Strong command of model evaluation, including designing evaluation suites, reasoning about overfitting and bias-variance tradeoffs, and systematically detecting and mitigating hallucinations.
• Solid understanding of modern model architectures, including transformers and diffusion models, with the judgment to decide when and how to apply them.
• Production MLOps experience, including model deployment, monitoring pipelines, and latency, cost, and reliability optimization in a live environment.
• Strong full-stack fundamentals with the ability to work across backend and frontend systems to ship complete, user-facing AI products.
• Exceptional communication skills with the ability to explain complex technical decisions clearly to engineers, product managers, and executives.
• Demonstrated product thinking, including the ability to ask whether something should be built before deciding how to build it.

Nice-to-haves

• Experience fine-tuning foundation models and a clear point of view on when fine-tuning outperforms prompting approaches.
• Familiarity with AI safety considerations, guardrail frameworks, and responsible deployment practices.
• Experience building agentic or multi-step reasoning systems using tools such as LangChain, LlamaIndex, or custom orchestration frameworks.
• Background in a SaaS or product analytics environment where user behavior data informs AI design.
• Prior experience contributing to or launching a net-new team or product area.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in New York, NY is $209,000 - $235,000.

Benefits: Highly competitive, employer-heavy coverage, including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

Staff AI Software Engineer

The Team + The Role

Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents.

As a Staff AI Software Engineer, you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly.

This role is based in our New York office.

What this looks like day-to-day

• Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users.
• Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers.
• Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early. You will implement guardrails that hold up under real-world usage and load.
• MLOps ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems are observable, performant, and production-ready.
• Full-stack delivery: Contribute across the stack when needed to get complete AI products in front of users. This team ships products, not just models, and you will help close the gap between technical capability and user experience.
• Product partnership: Partner closely with product and design to frame problems well before implementation begins. You will push back when the framing is wrong and help the team stay focused on what is worth building.
• Technical leadership: Stay current on the research and tooling landscape, including transformers, diffusion architectures, orchestration frameworks, and emerging agent patterns. You will bring relevant advances back to the team and help raise the technical bar.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Staff AI Software Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• Deep hands-on experience building and shipping LLM-powered systems, including retrieval-augmented generation, tool use, and agent orchestration frameworks.
• Demonstrated ability to set technical direction for AI systems across teams, establish architectural patterns, make foundational model strategy decisions, and raise the bar for AI engineering quality.
• Experience owning outcomes across team boundaries, including identifying capability gaps, driving alignment across engineering and product, and influencing how a broader organization approaches AI.
• Strong command of model evaluation, including designing evaluation suites, reasoning about overfitting and bias-variance tradeoffs, and systematically detecting and mitigating hallucinations.
• Solid understanding of modern model architectures, including transformers and diffusion models, with the ability to make informed decisions about when and how to apply them.
• Production MLOps experience, including model deployment, monitoring pipelines, and latency, cost, and reliability optimization in live environments.
• Strong full-stack fundamentals and comfort working across backend and frontend systems to ship complete, user-facing AI products.
• Exceptional communication skills, with the ability to explain complex technical decisions clearly to engineers, product managers, and executives.
• Demonstrated product judgment and the ability to evaluate whether something should be built before determining how to build it.

Nice-to-haves

• Experience fine-tuning foundation models and a clear point of view on when fine-tuning outperforms prompting-based approaches.
• Familiarity with AI safety considerations, guardrail frameworks, and responsible deployment practices.
• Experience building agentic or multi-step reasoning systems using tools such as LangChain, LlamaIndex, or custom orchestration frameworks.
• Background in a SaaS or product analytics environment where user behavior data informs AI product design.
• Prior experience contributing to or launching a net-new team or product area.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Pendo is a hybrid culture. In-office 3 days per week unless designated remote.

Compensation: The expected salary range for this role to be performed in New York, NY is $250,000 - $280,000.

Benefits: Highly competitive, employer-heavy coverage, including $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

The role:

SoFi’s Staff AI Engineer is a highly experienced, hands-on individual contributor within SoFi’s growing independent risk organization, focused on owning the design, development, and evolution of agentic AI systems to solve real-world, high-impact problems.

This role will be instrumental in architecting, building, and scaling AI systems that enhance risk management and internal workflows, with a focus on creating reliable, reusable, and production-grade solutions.

This role operates at the intersection of the intelligence layer, including LLMs, agents, and orchestration, and the experience layer, which defines how users interact with and derive value from AI systems. You will shape how these systems are designed and integrated into critical workflows, ensuring they are intuitive, reliable, and effective in high-stakes risk environments.

You will work closely with the Senior Manager of AI Engineering as well as business stakeholders, to translate complex, ambiguous problems into scalable, production-grade AI systems with measurable impact.

What you’ll do: 

• Architect and Develop Agentic AI Systems: Lead the design and development of AI systems that leverage multi-step reasoning, tool use, and structured workflows, using frameworks such as LangGraph or similar approaches. Incorporate planning, memory, tool integration, and adaptive control flow to enable automated decisioning, risk insights, and internal platforms.
• Design the Experience Layer: Define how users interact with AI systems by designing workflows, interfaces, and feedback loops that drive adoption, usability, and trust. THis will involve close coordination with users / stakeholders. Ensure alignment between system behavior and user expectations.
• Context Engineering and System Design: Define and implement approaches for structuring inputs, outputs, and system context to improve reliability and performance of LLM systems, including prompt design, retrieval strategies, and workflow composition.
• Productionize AI Systems: Develop production-grade services and APIs, integrate agents into real systems, and ensure scalability, reliability, and maintainability.
• AI Observability and Evaluation: Build tracing, debugging, and evaluation frameworks to understand system behavior and continuously improve agent performance.
• Cross-Functional Collaboration: Partner with risk, engineering, and business teams to translate ambiguous problems into working AI systems and deliver measurable outcomes.
• Proof of Concepts and Innovation: Innovation and Prototyping: Identify high-impact opportunities to apply AI, rapidly prototype solutions, and evaluate emerging tools and approaches to inform long-term system design aligned with latest trends in AI.

What you’ll need:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
• 7+ years of software engineering experience, with significant experience building and scaling AI-powered systems in production.
• Strong experience working with LLMs and building applications using prompting, APIs, and/or agent frameworks.
• Experience designing and implementing agentic systems, including patterns such as tool use, multi-step reasoning, and workflow orchestration.
• Deep experience in context engineering for LLM systems, including structuring inputs and outputs, prompt design, and retrieval-based approaches.
• Strong backend engineering experience, including building scalable services and APIs (Python preferred).
• Experience designing systems on cloud platforms such as AWS, Azure, or GCP, with an understanding of modern development and deployment practices.
• Experience working with structured and unstructured data, including building pipelines to support downstream AI applications.
• Experience defining and implementing evaluation frameworks for AI systems, including metrics, experimentation, and performance iteration.
• Strong system design skills, with the ability to architect scalable, reliable solutions.
• Ability to operate effectively in ambiguous problem spaces and translate them into well-defined systems.
• Strong communication and collaboration skills, with the ability to work cross-functionally and influence technical decisions.
• Demonstrated ownership mindset, with a track record of delivering high-impact systems end-to-end.

Nice to have:

• Experience designing and building user-facing workflows or internal tools powered by AI.
• Familiarity with observability and evaluation tools for AI systems such as Langfuse, LangSmith, or similar.
• Experience working in financial services or building systems for risk-related use cases.
• Experience with frontend technologies such as React for building AI-powered interfaces.
• Experience contributing to shared platforms, libraries, or internal tooling that enable reuse across teams.
• Experience building systems that require explainability, auditability, or operate in regulated environments.

This is Engineering at Lattice

At Lattice, we build software that helps people and organizations thrive. Our engineering team values maintainable systems, strong collaboration, and thoughtful product experiences.

As we expand AI-powered capabilities across our platform, security is a core part of how we design, build, and operate our product. Our Product Security team partners closely with engineering to ensure we ship features that are secure by default and resilient in production.

What You Will Do

You will work closely with product and platform engineering teams to improve the security of Lattice’s applications and services.

Product Security & Engineering Partnership

• Partner with engineers to identify, triage, and remediate security issues in product features and services
• Participate in security reviews and threat modeling for new features and systems
• Perform security-focused code reviews and help identify common vulnerabilities
• Contribute to secure-by-default patterns, libraries, and tooling in our TypeScript-based stack

Security Tooling & Operations

• Help implement and operate security tooling (SAST, DAST, dependency scanning, etc.)
• Support vulnerability management workflows, including internal findings and bug bounty reports
• Assist in investigating security issues and assessing risk and impact

Cloud & Platform Security

• Collaborate with platform and infrastructure teams to improve application and cloud security posture
• Contribute to improving security practices in AWS-based environments

AI/LLM Security

• Assist in identifying and mitigating risks in AI/LLM-powered features, including prompt injection, data leakage, and unsafe output handling
• Apply emerging best practices (OWASP Top 10 for LLM Applications) to real product use cases

Security Enablement

• • Contribute to security guidance, documentation, and training for engineering teams
  • Help improve how security is integrated into the development lifecycle

What You Will Bring to the Table

Experience that is important for you to have at some level:

• 1–3+ years of experience in product security, application security, or software engineering
• Experience writing and maintaining code in JavaScript/TypeScript (or similar languages like Python or Ruby)
• Familiarity with common web and API vulnerabilities (e.g., OWASP Top 10)
• Exposure to security testing tools (SAST, DAST, dependency scanning, etc.)
• Experience working in or with cloud environments (AWS or similar)

Technical Approach

• Ability to identify common security risks and suggest practical mitigations
• Understanding of secure coding practices and basic security controls
• Interest in how security decisions impact real-world product systems

Collaboration & Growth

• Strong communication skills and ability to work closely with engineering teams
• Willingness to ask questions, learn quickly, and take ownership of well-scoped problems
• Ability to contribute to team discussions and share security context effectively

Experience that would be nice to have:

• Experience with modern web architectures (Next.js, NestJS, GraphQL)
• Familiarity with containerization or Kubernetes
• Experience or interest in AI/LLM security, including

----

The estimated annual cash salary for this role is $116,500 - $154,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Vision insurance; Life, AD&D, and Disability Insurance; Emergency Weather Support; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Commuter & Parking Accounts; Lunches in the Office; Internet and Phone Stipend; 401(k) retirement plan; Financial Planning; Learning & Development Budget

*Note on Pay Transparency:

Lattice provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience.

Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

#LI-remote

Octus delivers breaking news and market-moving intelligence through cutting-edge data and technology for hedge funds, investment banks, and law firms- and we’re transforming how professionals access complex and opaque information. As part of our high-performing AI Innovation team, you’ll help design, build, and productionize modern GenAI and LLM-powered systems that support both client-facing features and internal operational efficiency. You’ll work end to end—from shaping ambiguous problems into scalable solutions to deploying reliable AI models in production - collaborating closely with product, engineering, and infrastructure teams. This is a hybrid role based in NYC (3 days in office per week). Curious about what we’re building? Check out our flagship GenAI product, CreditAI here and our AI framework here.

Responsibilities

• Apply strong problem-solving and critical thinking skills to break down complex, ambiguous requirements into clear, implementable technical components and system designs.
• Design, build, and maintain AI-powered and data-driven systems with a focus on modern language and multimodal models, including LLM-driven applications, RAG pipelines, and agentic workflows.
• Evaluate and productionize commercial and open-source LLMs, choosing appropriate models, tools, and techniques for each use case. Develop multi-step agentic workflows that incorporate tools, external data sources, memory, and control logic.
• Manage the orchestration of production LLM workflows and agentic systems, ensuring reliability and efficiency through prompt routing, state management, retries, fallbacks, and error handling. Design, test, and iteratively refine prompts and system instructions using prompt engineering and tuning techniques to improve model reliability, accuracy, and task performance.
• Maintain production-grade code and services with automated monitoring and performance tracking, using metrics and alerts to guide continuous improvements in models, prompts, and pipelines.
• Apply systems thinking to design and optimize AI and LLM systems, balancing quality, scalability, latency, cost, and operational complexity, while implementing efficiency improvements using model selection, prompt design, batching, caching, and retrieval strategies.
• Define and implement evaluation and observability frameworks for AI systems, including automated testing, task-specific benchmarks, regression testing for prompts, human-in-the-loop validation, and performance monitoring.
• Build and integrate AI models into backend systems and APIs to support both real-time and batch inference, ensuring solutions are production-ready, scalable, and efficient.
• Apply NLP and ML techniques to tasks such as information extraction, semantic search and retrieval, text classification, summarization, and reasoning over text and documents.
• Collaborate closely with engineering and infrastructure teams to deploy solutions using containerized and cloud-based environments (e.g., GitHub, Docker, AWS), applying modern deployment and infrastructure practices.
• Collaborate with product managers, business stakeholders, and domain experts to translate complex, ambiguous business problems into actionable technical solutions, and communicate progress, trade-offs, and outcomes to relevant stakeholders.
• Continuously learn and adapt to advancements in NLP and Generative AI to ensure solutions remain innovative and effective.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• 3+ years of experience as a Data Scientist, Machine Learning Engineer, or applied AI practitioner, with a strong foundation in computer science, algorithms, and software development. 
• Advanced programming skills in Python, with experience building production-grade systems beyond research or experimentation.
• Solid understanding of machine learning and applied AI concepts, with experience taking solutions from prototype to production.
• Hands-on experience designing, building, and deploying LLM-driven or GenAI applications, including familiarity with vector databases, embeddings pipelines, or semantic search systems.
• Practical experience with cloud-based deployments and infrastructure tools (e.g., AWS, Docker, GitHub) and an understanding of modern DevOps practices, containerization, orchestration, caching strategies, and cost-aware design.
• Strong problem-solving skills and systems thinking, with the ability to balance trade-offs across model quality, scalability, inference latency, cost, and operational complexity.
• Ability to interpret and implement research ideas and algorithms, actively contributing to research and development initiatives while translating them into production solutions.
• Excellent communication and collaboration skills, with experience working closely with product managers, engineers, and domain experts to deliver actionable technical solutions.
• Passion for learning and staying current with the rapidly evolving AI/ML landscape, including emerging best practices for GenAI applications.
• Strong ownership and initiative, with the ability to independently drive projects from problem definition to delivery, while being a team player and contributing to the overall success of the data science team.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $130,000-$145,000.

The actual compensation will be at Octus’ sole discretion and will be determined by the aforementioned and other relevant factors. This position is eligible for a performance-based annual bonus.

What we do  

You’ll join a software engineering team building internal AI solutions that support teams across The Trade Desk. We leverage large language models, retrieval‑augmented generation (RAG), agentic systems, and enterprise platforms like Microsoft Copilot and Anthropic Claude to improve productivity, streamline workflows, and reduce operational friction.

Our team also plays a key role in AI enablement across the company—supporting teams as they adopt Copilot, Claude and similar tools, designing and deploying custom AI agents, and guiding partners through their AI journey from idea to impact.

As a Senior AI Engineer on this team, you’ll be an end-to-end owner—collaborating closely with stakeholders, identifying opportunities, and delivering tools that make a real impact. We’re a nimble, fast-paced, and highly collaborative group that thrives on transforming the way teams operate and driving greater value across The Trade Desk.

What you’ll do: 

Some of the work that you will be doing to help us deliver on our mission is:

• Design and deploy intelligent agentic systems that integrate large language models (LLMs) with enterprise data, tools, and workflows using frameworks like LangChain, LlamaIndex, and Semantic Kernel.
• Develop Retrieval-Augmented Generation (RAG) applications using tools like Azure AI Search, vector databases, and secure enterprise connectors to deliver contextual insights.
• Build and deploy agents using Microsoft Copilot, Copilot Studio, Anthropic Claude, and similar platforms to help teams operationalize solutions within enterprise guardrails.
• Build and iterate on conversational agents that solve real-world problems, meet stakeholder needs, and deliver measurable business value.
• Deliver high-impact features by collaborating across teams, leading through ambiguity, and aligning technical solutions with business goals.
• Drive quality and performance through automated testing, monitoring, and data-driven evaluation of success criteria, user adoption, and operational efficiency.
• Mentor teammates and contribute to a culture of innovation, technical excellence, and continuous learning.

Who you are: 

• You have a Bachelor’s/Master’s level degree in computer science or relevant engineering-related field or equivalent experience.
• You have 8-10+ years of software engineering experience, including 1-2+ years working on AI-powered systems or products.
• You are proficient in Python and comfortable with additional languages such as C#, SQL, or TypeScript/React.
• You’re excited about AI enablement, including helping teams adopt platforms like Microsoft Copilot, Anthropic Claude and Copilot Studio, building agents, and guiding others through their AI journey.
• You have a good foundational knowledge of or hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and prompt engineering using LLM APIs.
• You have experience productionizing applications and implementing CI/CD pipelines to ensure reliable, scalable deployments.
• You are skilled in data ingestion and transformation using APIs, ETL pipelines, and connectors, and familiar with vector databases and retrieval strategies.
• You communicate clearly across technical and non-technical audiences and thrive in a collaborative, cross-functional environment.
• You are a fast learner who adapts quickly to new technologies and solves complex problems with creativity and pragmatism.

#LI-TP1

A variety of technical opportunities is one of the best things about working at The Trade Desk as a software engineer, which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We are not seeking engineers who know all the answers; we need engineers who can invent answers no one has thought of yet and find answers to the questions yet to be asked. 

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

[LA JOBS ONLY] The Trade Desk will consider qualified applicants with criminal histories for employment in a manner consistent with the requirements of the Los Angeles Fair Chance Initiative for Hiring, Ordinance No. 184652.

[SF JOBS ONLY] Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#LI-TP1

Your Opportunity

Scion is paving a path in student living and the Facilities Manager is a keystone team member in the execution of our vision. This position ensures safety and functionality of the property’s buildings and equipment and ensures optimal service is carried out by the onsite Facilities team and any third-party vendors.

The Facilities Manager is a subject matter expert and experienced leader who excels in a fast-paced, agile, collegiate environment. This role demands superior problem solving, leadership and unwavering follow through. Those in the Facilities Manager position may also be asked to assist other properties.

Your Benefits

• FLSA Status Exempt
• Discretionary annual bonus
• Paid Time Off + Floating Holidays
• Health Insurance
• Dental Insurance
• Vision Insurance
• 401k Matching
• Paid Parental Leave
• Learning reimbursement opportunities

Your Responsibilities 

• Manage all building services and preventative maintenance programs to the best of industries practices, the Scion’s Standard Operating Procedures, and in compliance with the State/Federal Govt./OSHA’s Codes/regulations.
• Manage the day-to-day operations including but not limited to heating, ventilating, air conditioning (HVAC), plumbing and piping, fire protection, and general building maintenance and troubleshooting, building automation systems and building maintenance
• Monitor systems and provides diagnostics, preventative maintenance, annual testing, permitting, certification for all major building systems including, but not limited to: chilled water systems with fan coil units, air handling units with outside condensers including roof top units (RTU), building stationary boilers, hot & cold water distribution systems (plumbing, pressure/pneumatic/storage tanks, variable frequency drive (and pumps & motors), domestic hot water heaters, building automation systems (BAS), electrical distribution systems, switchgears and controls, generators, uninterrupted Power supply (UPS), elevators and lifts, parking structures (ventilation/drainage Systems, T-Joints), entrance & exit Gates and overhead doors, shingled/tarred roof, TPO membrane roofing system, EIFS, brick, vinyl, & cementitious sideboard, ACP, curtain walls, insulated glass units (IGUs).
• Operate and manage all life safety systems including fire pumps, fire alarm monitoring panels, dry/wet sprinkler systems, visual and audible alarms, back flow preventers, smoke detectors, CO2 sensors/alarms, fire extinguishers, emergency lighting, means of egress, fire
• Prioritize and schedule maintenance work, assuring quality of work consistent with Scion’s standards.
• Manage the Facilities Technicians to ensure all service requests are completed within Scion standards and are appropriately and accurately
• Manage facilities budgets.
• Review completed work to verify conformance to standards or repair
• Ensure all emergency, routine maintenance/repairs are carried out in a timely and professional manner.
• Ensure all Preventive maintenance is carried out in a timely and professional manner.
• Respond promptly and effectively to all safety/risk-management-related issues at the
• Review completed work orders for accuracy of labor hours, materials’ cost, and track recurring equipment failures.
• Conduct regular inspection tours of buildings, interior common areas and the exterior of the property, equipment and surrounding grounds for deficiencies, potential safety, health, or code problems and necessary
• Prepare written reports summarizing findings, and advises other building users as appropriate, of the
• Provide recommendations for dealing with problems noticed in
• Oversee and supervise “Turn” preparation including the prompt inspection of vacated units, makes appropriate repairs and charges, and ensures completion as
• Inspect vacant units after repairs and maintenance have been completed to determine quality of work performed and readiness for
• Manage the maintenance spare parts and the tools inventory, determining which parts/tools to stock and their stock level and working directly with General Manager to maintain inventory of parts, tools, and supplies within
• Maintain shop appearance and all mechanical, supply, electrical and storage facilities on
• Ensure proper maintenance of equipment to ensure warranty compliance and extended useful life.
• Oversee all other contracted work in the building, obtaining bids and negotiating prices with vendors and contractors, as approved by the General Manager, Regional Manager or the Regional Facility Manager.
• Coordinate deliveries, schedules, and performance of all facility related
• Ensure proper safety procedures are followed, personal protective equipment is used, and health & safety policies are
• Manage process for keying and coring/coding of locks and maintain lock procedures, logbooks and protocols for key management and
• Effectively implement standard operating procedures and preventive maintenance programs according to Scion’s
• Take part in emergency preparedness planning and acts as essential personnel in
• Escalate unique or urgent repairs/replacements to General Manager and Regional Facilities Manager.
• Maintain records on all major systems including maintenance manuals, manufacturer’s cut sheets, warranties, and equipment
• Work closely with the General Manager and Regional Facilities Manager to manage, formulate and track facilities and capital
• Hire, train and develop Facilities team members, holding them accountable for delivering a high level of

The responsibilities listed above may not be all-inclusive.

What We Require

• High school diploma/GED, trade school diploma, or military training
• 8 years of relevant experience managing building system in multi-unit residential properties, 5 years of supervisory experience
• 5 years’ experience with building automation systems, and life safety systems
• EPA 608 Universal certification
• HVAC/EPA 608 Universal certification
• Certified Pool Operator (CPO), or intention to obtain within six months
• Expertise in plumbing, HVAC, electrical and mechanical systems as well as generally accepted maintenance practices
• Boiler operator or Stationary Engineer Certificate/License
• Ability to read and interpret documents such as design drawings, blueprints, safety guidelines, operating and maintenance instructions and procedural manuals
• Ability to manage multiple projects simultaneously, set priorities and meet deadlines
• Basic computer working knowledge, including Microsoft Office and CMMS
• Valid driver’s license
• Ability to stand 8 hours or longer per day and lift up to 100 lbs. as necessary

 Operational Details

• Job location is at the assigned property. May be required to travel periodically.
• Serves in an “on-call” capacity, except during approved PTO periods.

The Scion Group LLC provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, religion, creed, national origin, color, gender, sex, sexual orientation, gender identity or expression, age, physical or mental disability (as long as the employee/applicant is otherwise qualified for the job with or without a reasonable accommodation), genetic information, HIV/AIDS status, marital status, uniformed service, veteran status, pregnancy or other legally protected status or category under federal or state law. The Scion Group LLC complies with applicable state and local laws governing nondiscrimination in employment in all locations in which the Company has properties. This policy applies to all terms and conditions of employment, including hiring, placement, promotion, termination, layoff, recall, transfers, leaves of absence, compensation, training and other terms and conditions of employment. The Scion Group LLC is committed to the principles of equal employment opportunities.

IND5 #wearehiring #werehiring

Role Description

• As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.

• Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for enterprise-grade supply chain environments.

• Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

We're a new team building AI-assisted product experiences that help Datadog customers go from investigation to action, by enabling conversational workflows, guided remediations, and codefixes that address the root cause of production issues.

We're looking for a product-minded engineer to help us quickly define and ship applied AI experiences across chat, remediations, and codefixes. This role sits at the intersection of backend engineering, product development, and prompt engineering, with a strong emphasis on building reliable, production-quality AI systems.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You'll Do:

• Work closely with product managers, designers, and engineers to build and iterate on AI-powered product experiences in Bits AI SRE.
• Develop customer-facing systems across chat, remediations, and codefixes that help users resolve production issues more quickly.
• Work on prompts, evaluation loops, and backend systems to make applied AI workflows reliable, useful, and production-ready.
• Prototype quickly, test what works in the real world, and iterate rapidly to ship new product capabilities.
• Build the infrastructure and product logic needed to connect AI outputs to meaningful actions, including operational remediations and generated code changes.
• Collaborate with partner teams across Datadog to expand remediation capabilities and integrate with systems that support investigation, automation, and code generation.
• Follow the latest developments in LLM prompting, agent design, and applied AI product development, and bring strong judgment about what is practical to use in production.

Who You Are:

• You're an engineer with at least 5 years of professional experience, with strong backend engineering skills and a product mindset. You have experience building production systems in Go (or similar) and have worked with LLM-based systems in practice.
• You are excited about applied AI and motivated by building product experiences that help users take meaningful action, not just generate insights.
• You have experience with prompt engineering, evaluation, and iteration for LLM-powered systems, and know how to improve quality through experimentation and feedback.
• You have strong engineering fundamentals and can build the systems needed to productionize AI features, including integrating model behavior into reliable user-facing products.
• You are comfortable operating in a fast-moving environment with high ambiguity, and enjoy prototyping, learning quickly, and shipping early versions of new ideas.
• You collaborate well with cross-functional partners and can work effectively with product, design, and engineering to shape both the user experience and the technical implementation.
• You care about product quality and user outcomes, and can balance speed with pragmatism when building new AI-powered workflows.
• Bonus: you have experience with Kubernetes or systems related to production remediation and operational automation.
• Requirement - Demonstrated ability to use AI coding tools in day-to-day workflows and validate, critique, and refine AI-generated output.
• Plus - You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products.

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

To conform to US export control regulations, candidates should be eligible for any required authorizations from the US government. This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government.

#LI-Hybrid

JOB SUMMARY

The Field Service Supervisor will be responsible for managing the field service engineers, helping to ensure our client’s onsite visits are proactive and filled with valuable work. This role reports to the Service Delivery Deputy Director responsible for service center. 

KEY RESPONSIBILITIES

• Help lead and prioritize the support team's workload.
• Visit our client sites at least 3 times per week and ensure that our engineer’s work product is aligned with clients and CTS expectations. 
• Liaise with internal teams, vendors, and client contacts. 
• Act as a resource to the rest of the team for rapid decisions and direction as well as help to coordinate escalations.
• Help identify areas where Standard Operating Procedures (SOP's) don't exist or need further work. In addition, to help improve those processes.
• Regularly monitor the teams' overall performance and report on metrics to the CM’s, SA’s, and SDM’s. Participate in efforts to improve different level engineer group performance (e.g. manage dashboards, SLA’s, KPI’s. risks/issues).
• Be a liaison to clients where it relates to service delivery issues.
• Ensure that proactive work is being carried out by engineers in addition to the day-to-day service requests/incidents). 
• Identify areas of needed coaching and training for the team.  
• Listen to the teams overall internal and client facing feedback and help resolve any conflicts and issues..
• Manage overall expectations of our clients via phone, email, tickets or any other method approved and used by CTS.
• Ensure the team follows established procedures for routine work like creating new users, configuring laptops/desktops, NVR’s, PBX’s, and phones.
• Ensure the prompt and thorough documentation of all work by the team via our ticketing system, ITGlue and other tools. This includes supporting the team with documenting assets, configurations, passwords, processes, etc and maintaining current and accurate documentation.
• Ensure the consistency and efficiency of our documentation efforts. Support the team with documenting assets, configurations, passwords, processes, etc. and maintaining current and accurate documentation.
• Keep track of supervised engineers' efforts, their successes and failures and provide acknowledgement where there is success as well as support and direction where there is failure.
• Review onsite engineers EOD reports to ensure quality of work and compliance with our standards  
• Review all supervised engineers ticket communication where time allows but definitely on a weekly basis
• Work closely with the Client Strategy teams and also participate in the preparation of the QBRs (Quarterly Business Review) when requested in order to assist with managing the relationship and service offerings to the client. 
• Have 1 on 1’s with supervised engineers and provide clear metrics of their overall performance. Lastly, ensure engineers are fulfilling expected output hours and quality of work. 
• Provide onsite assistance when a client is experiencing frustration with our overall services. 
• Identify & Lead Initiatives to Improve on all KPIs & Performance Metrics alongside the SDM.
• Accountable to KPIs & Metrics that will include things such as Client Satisfaction Scores (CSAT), SLA’s, Team Efficiency, Team Happiness as well as intangible metrics that align with things such as our Company Core Values

REQUIRED SKILLS AND QUALIFICATIONS

• 5+ years of experience in a customer-facing, technical-services environment, with a strong commitment to customer service. 
• Great communication skills, founded in being a good listener who seeks to understand the position of those being supported.
• Experience in Scheduling and Resource Management.
• Experience in networking protocols: TCP/IP, BGP, OSPF, VPN, IPSEC, VoIP and QoS.
• Experience with WAN/LAN networking including routing, switching, security and load balancing.
• Experience in WLAN technologies including, but not limited to, Meraki, UniFi and Cisco.
• Experience with Microsoft Windows Server, Windows Desktop and Apple Ecosystems.
• Experience in Network Attached Storage (NAS). 
• Experience with Grand Stream or other Asterisk based PBX systems.
• Experience with Android, iOS, Gsuite and Office365.

PREFERRED SKILLS AND QUALIFICATIONS

• Experience working for a Managed Service Provider (MSP) or IT Support Business.
• Experience with MSP-related tools: ConnectWise, Kaseya VSA, PRTG, and ITGlue.

LOCATION

This is a full-time mainly onsite position in the New York Metro area with the ability to work remotely some days per week (dependent on client needs). Some night and/or weekend work may at times be required. Lastly travel to other states (although rare) may be required as we expand to other states. 

COMPENSATION

The annual salary range for this role is $100,000 to $120,000.

BENEFITS

• Competitive compensation
• Health Insurance (medical, vision, dental), 80% covered for employee-only plans and 75% covered for employee-spouse, employee-kids, and employee-family plans
• Flexible Spending Account (FSA)
• Health Savings Account (HSA)
• Employee Assistance Program (EAP)
• Retirement Plan (401(k)) with company match
• Commuter Benefits
• Short-Term Disability Insurance fully paid by the company
• Long-Term Disability Insurance fully paid by the company
• Life and AD&D Insurance, with optional Supplemental Life Insurance
• Paid Time Off, including Paid Parental Leave
• 10 Holidays
• 2 Floating Holidays

CTS participates in the E-Verify Program. As part of this program, the company provides the federal government with your Form I-9 information to confirm your employment eligibility in the United States.
Learn more at www.e-verify.gov (information available in English and Spanish).

About the Role:

CoreWeave is seeking a Staff AI Security Engineer to define and operationalize security across our AI ecosystem. This role sits at the intersection of AI/ML, cloud infrastructure, and security engineering. You'll build secure-by-default foundations for AI development, agentic workflows, and enterprise AI adoption, balancing velocity with strong security guarantees. You will also partner closely with enterprise security and IT teams to manage AI-adjacent risks across the corporate environment, including shadow AI, data exfiltration through AI tooling, and SaaS security posture for AI-enabled platforms.

What You'll Do:

• Design and implement security controls across AI/ML infrastructure, including model artifact storage, data lineage and integrity, model signing and provenance, and ML pipeline security (MLOps/MLSecOps)
• Develop AI security policies, standards, and threat models covering model development, training pipelines, data ingestion, inference environments, and agentic systems
• Build security guardrails for agentic workflows: tool access and permissioning, input/output validation, execution boundaries, sandboxing, and auditability of agent actions
• Lead secure adoption of AI tools across engineering, security, operations, and enterprise functions. Evaluate AI vendors, copilots, and integrations. Define policies for data sharing, model usage boundaries, and sensitive data handling in prompts and outputs
• Partner with enterprise security and IT on AI-related risks across the corporate environment, including endpoint posture, corporate identity, and SaaS security for AI-enabled platforms
• Conduct threat modeling and adversarial testing of AI systems, covering prompt injection, data poisoning, model extraction, and backdoored models. Build and maintain a CoreWeave-specific AI threat taxonomy
• Drive cross-team technical decisions and influence architecture across platform engineering, security engineering, ML/AI teams, and product/DevEx to embed security into AI platforms and developer tooling

Who You Are:

Minimum Qualifications

• 10+ years of experience in security engineering (cloud, application, or infrastructure)
• Experience with AI/ML systems: LLMs, training pipelines, inference systems, or MLOps
• Strong, demonstrable experience building and securing large-scale distributed systems
• Strong coding skills in Go, Python, or similar
• Familiarity with Kubernetes, containerized environments, and cloud platforms (AWS, GCP, Azure)
• Understanding of AI-specific threats: prompt injection, data leakage, model misuse, supply chain risks in models and datasets
• Track record of driving cross-team technical initiatives and influencing architecture decisions at the org level

Preferred:

• Experience building or securing LLM-based systems, agent frameworks (LangChain, etc.), or AI-powered internal tools
• Background in adversarial ML or red teaming AI systems
• Experience with secure model deployment pipelines or confidential computing / secure enclaves
• Familiarity with identity and access control systems
• Experience in high-performance or GPU-centric environments
  
  

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.

Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs.

We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions.

This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business.

Responsibilities:

• Develop and deploy ML models across multiple problem domains — including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection — in production environments serving millions of rides
• Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead
• Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform
• Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale
• Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement
• Identify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions
• Contribute to team engineering standards — code quality, observability, documentation, and testing practices

Experience:

• Experience with GenAI / LLM ecosystems — prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning
• Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis)
• Experience with pricing, marketplace, or fraud-related ML problems
• Familiarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms
• Track record of identifying and scoping ML projects independently, not just executing on pre-defined specs

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $176,000-$211,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Every day, millions of riders and drivers depend on Lyft — and when something goes wrong, we want to make it right as fast as possible. The Self-Serve Intelligence team within Safety & Customer Care org is building the AI-powered systems that do exactly that: resolving rider and driver suboptimal experiences without agent involvement through intelligent solutions in AI Assist (e.g. AI Agents), automations, and self-serve workflows. We're building backend systems, APIs, and AI-powered products that fundamentally rethink how customers get help — combining robust engineering with GenAI to deliver reliable, scalable self-serve experiences.

As a Senior Software Engineer on the Self-Serve Intelligence team, you will design, build, ship, and maintain backend services and AI-powered products (e.g. various AI Agents) that autonomously resolve customer suboptimal experiences. You'll own the full lifecycle — from system design and prototyping through production deployment and operational excellence — partnering with product, design, data science, and operations to deliver high-quality, reliable solutions at scale.

Responsibilities:

• Design, build, ship, and maintain scalable backend services and GenAI-powered products (e.g. AI Agents) that resolve rider and driver suboptimal experiences autonomously
• Develop robust evaluation frameworks to measure and improve the quality and impact of GenAI-driven customer experiences
• Lead projects from idea to production, owning end-to-end system design, implementation, and operational health
• Write well-crafted, well-tested, readable, maintainable code
• Design and evolve APIs, data models, and service architectures that support rapid product iteration
• Rapidly adopt and integrate emerging AI capabilities to accelerate development velocity across the team
• Incorporate considerations for edge cases, failure modes, and business context into system design
• Participate in code and architecture reviews to ensure quality and distribute knowledge
• Own system reliability — monitor, debug, and improve service health, latency, and availability
• Proactively participate in resolving ongoing incidents
• Unblock, support, and effectively communicate across teams to achieve results
• Share your knowledge by giving brown bags, tech talks, and evangelizing engineering and AI best practices

Experience:

• 5+ years of software engineering industry experience
• Strong backend engineering fundamentals — designing, building, and operating distributed systems and microservices in production
• Hands-on experience with LLMs, agentic workflows, or building AI Agents — we value depth of AI experience and treat it as a strong differentiator
• Track record of building, evaluating, and shipping GenAI or ML-powered products
• Experience defining API schemas and developing backend services in a microservices environment
• When facing an ambiguous problem or outside your expertise, you can quickly learn what you need to dig in, make sense of it, and start working toward a solution
• You're a great communicator who can advocate for your proposals while empathizing with your teammates' goals and priorities
• You have a history of going out of your way to help your fellow engineers be more productive

It would be a huge plus to have:

• Strong proficiency in Python
• Experience with AI agent frameworks, prompt engineering, or model evaluation pipelines

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $185,000 - $222,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

We're looking for a Staff Software Engineer with deep experience in AI/ML to join the Notebooks team. Datadog Notebooks provide a flexible tool for ad-hoc data analysis, collaborative investigations, and technical documentation. Its fluidity makes it an ideal surface for agents and humans to interact. The Notebook team is building AI-driven workflows for natural-language data analysis, assisted graph generation, automated investigations, and more. You will act as a technical leader in this domain, focused on building industry-leader AI-powered features. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Spearhead AI initiatives within Notebooks, serving as the technical owner for the design, development, and deployment of ML/AI-driven features.
• Shape the long-term technical direction and strategy for AI workflows within Notebooks and related products.
• Champion the full development cycle: from rapid prototyping and defining success metrics/evaluations to running experiments, iterating, and achieving production-ready scale and reliability.
• Drive product direction with a strong user focus, always advocating for the best end-user experience.
• Coordinate with other leaders and product teams interested in leveraging Notebooks in their AI-powered workflows.
• Develop robust agent systems, including tools, retrieval and planning strategies, guardrails, prompt management/evaluations, fallbacks, and human-in-the-loop processes.
• Stay up to date with industry trends, guiding the adoption of new technologies and evolving best-practices.

Who You Are:

• You have a BS/MS/PhD in a scientific field or equivalent experience
• 10+ years of relevant engineering experience, as well as experience acting as a technical lead
• Proven track record of leading large-scale AI/ML initiatives in a product-driven environment
• You have significant experience in model deployment, development, training, fine-tuning, and evaluation

• You are passionate about mentoring others and cultivating a high-performing engineering culture.
• You’re excited about leveraging AI tools to enhance how you code, solve problems, and build

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Generous and competitive benefits package
• New hire stock equity (RSUs) and employee stock purchase plan
• Continuous career development and pathing opportunities
• Employee-focused best in class onboarding
• Internal mentor and cross-departmental buddy program
• Friendly and inclusive workplace culture
  
  

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.

Datadog’s LLM Observability product enables organizations to monitor, troubleshoot, and optimize large-scale LLM-powered applications with confidence, while meeting requirements around data privacy, compliance, and cost management. As a Product Solutions Architect, you will partner closely with Datadog customers and the LLM Observability product team to design architectures, implement best practices, and drive adoption of LLM observability across customer environments.

At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Serve as the in-house subject matter expert for Datadog’s LLM Observability product
• Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting LLM Observability
• Create high-impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community
• Build proofs of concept and small-scale deployments to validate solutions and reproduce real-world customer environments
• Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience

Who You Are: 

• You bring a strong software engineering foundation, with hands-on experience building and operating LLM-powered applications in production environments, and are comfortable diving deep into codebases to understand architectural decisions, tradeoffs, and implementation details
• You are familiar with distributed systems and core observability concepts, such as tracing, metrics, and logging, and can translate those patterns into the emerging LLM observability domain, including LLM spans, evaluations, and prompt templates
• You have experience with languages such as Python and/or JavaScript/TypeScript
• You are comfortable operating in rapidly evolving, ambiguous technical domains
• You build deep context across teams and translate it into reusable, scalable solutions
• You take ownership from problem definition through implementation and measurable outcomes
• You are highly detail-oriented, particularly when working on architectures and customer-facing technical assets
• You bring strong listening and consultative skills and are experienced supporting customers in high-pressure, complex situations
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train, or air up to 40% of the time 

Bonus Points:

• Successful track record with 5+ years experience working as an Architect or Consultant 
• Experience using Datadog and/or other observability tools in an SRE or DevOps capacity
• Experience with LLM application evaluation and testing frameworks

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence.

As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production.

Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Drive design and implementation of LLM observability features.

• Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems
• Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit
• Develop and extend tools for tracing, evaluating, and debugging LLMs
• Influence architecture decisions and mentor engineers to build resilient, high-performance systems
• Stay close to customer pain points and use those insights to guide product and engineering priorities
• Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team

Who You Are:

• You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience
• Deep understanding of distributed systems and scalable backend architectures
• Hands-on experience building and shipping LLM-powered or GenAI applications. 
• Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering
• Ability to thrive in ambiguous, fast-changing spaces and have a product-oriented mindset
• You’re excited to shape the next generation of AI observability tools from the ground up
• Communicate clearly, think rigorously, and take pride in clean, maintainable code
• Experience with observability tools/platforms

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth:

• Get to build tools for software engineers, just like yourself. And use the tools we build to accelerate our development.
• Have a lot of influence on product direction and impact on the business .
• Work with skilled, knowledgeable, and kind teammates who are happy to teach and learn
• Competitive global benefits
• Continuous professional development

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Hybrid

ABOUT THE ROLE:

As a Sr. Full Stack Engineer (AI) at Rightway Healthcare, you'll spearhead our AI integration initiatives to revolutionize healthcare delivery through our platform. Working with a dynamic team, you'll drive the development of AI-powered features that empower members to make informed healthcare decisions, ensuring they get the right care at the right time and price. This role offers a unique blend of autonomy and innovation, where you'll transform cutting-edge AI concepts into production-ready solutions. While AI is a key focus, you'll also architect and implement solutions that scale across our platform, combining intuitive technology with expert guidance to bring clarity and direction to our members' healthcare journeys.

WHAT YOU’LL DO:

• Pioneer AI-driven solutions that enhance our care navigation and PBM services, directly improving healthcare outcomes for our members
• Lead rapid prototyping cycles, transforming concepts into production features within days or weeks, not months
• Architect and implement full-stack solutions using our modern tech stack (Node.js, React, TypeScript, Ruby, GraphQL, Postgres)
• Drive technical decisions independently while collaborating with cross-functional teams to ensure alignment with business goals
• Build and maintain scalable, production-grade systems that handle sensitive healthcare data with reliability and security
• Establish technical standards and best practices for AI integration across the platform
• Mentor team members and contribute to our engineering culture of innovation and excellence

WHO YOU ARE:

• A versatile full-stack engineer with 5+ years of experience building production applications at scale
• A self-driven problem solver who thrives in ambiguous environments and creates structure from chaos
• An innovative thinker who balances quick experimentation with production-quality implementation
• A technical leader comfortable making independent decisions while valuing team collaboration
• An effective communicator who can translate complex technical concepts for diverse audiences
• A pragmatic engineer who values shipping working solutions over perfect solutions
• Someone passionate about using technology to solve real healthcare challenges

EXTRA CREDIT:

• Experience designing and implementing AI/ML features in production environments
• Proven track record of optimizing LLM implementations and prompt engineering
• Background in healthcare technology or experience with HIPAA compliance

SALARY (BEFORE BONUS POTENTIAL):  $175,000 - $190,000 + bonus + equity

CYBERSECURITY AWARENESS NOTICE

In response to ongoing and industry-wide fraudulent recruitment activities (i.e., job scams), Rightway wants to inform potential candidates that we will only contact them from the @rightwayhealthcare.com email domain. We will never ask for bank details or deposits of any kind as a condition of employment. 

ABOUT RIGHTWAY:

Rightway is on a mission to harmonize healthcare for everyone, everywhere. Our products guide patients to the best care and medications by inserting clinicians and pharmacists into a patient’s care journey through a modern, mobile app. Rightway is a front door to healthcare, giving patients the tools they need along with on-demand access to Rightway health guides, human experts that answer their questions and manage the frustrating parts of healthcare for them.

Since its founding in 2017, Rightway has raised over $130mm from investors including Khosla Ventures, Thrive Capital, and Tiger Global at a valuation of $1 billion. We’re headquartered in New York City, with a satellite office in Denver. Our clients rely on us to transform the healthcare experience, improve outcomes for their teams, and decrease their healthcare costs.

HOW WE LIVE OUR VALUES TO OUR TEAMMATES:

We’re seeking those with passion for healthcare and relentless devotion to our goal. We need team members that embody our following core values:

1) We are human, first
Our humanity binds us together. We bring the same empathetic approach to every individual we engage with, whether it be our members, our clients, or each other. We are all worthy of respect and understanding and we engage in our interactions with care and intention. We honor our stories. We listen to—and hear—each other, we celebrate our differences and similarities, we are present for each other, and we strive for mutual understanding.

2) We redefine what is possible
We always look beyond the obstacles in front of us to imagine new solutions. We approach our work with inspiration from other industries, other leaders, and other challenges. We use ingenuity and resourcefulness when faced with tough problems.

3) We debate then commit
We believe that a spirit of open discourse is part of a healthy culture. We understand and appreciate different perspectives and we challenge our assumptions. When working toward a decision or a new solution, we actively listen to one another, approach it with a “yes, and” mentality, and assume positive intent. Once a decision is made, we align and champion it as one team.

4) We cultivate grit
Changing healthcare doesn’t happen overnight. We reflect and learn from challenges and approach the future with a determination to strive for better. In the face of daunting situations, we value persistence. We embrace failure as a stepping stone to future success. On this journey, we seek to act with guts, resilience, initiative, and tenacity.

5) We seek to delight
Healthcare is complicated and personal. We work tirelessly to meet the goals of our clients while also delivering the best experience to our members. We recognize that no matter the role or team, we each play a crucial part in our members’ care and take that responsibility seriously. When faced with an obstacle, we are kind, respectful, and solution-oriented in our approach. We hold ourselves accountable to our clients and our members’ success.

Rightway is PROUDLY an Equal Opportunity Employer that believes in strength in the diversity of thought processes, beliefs, background and education and fosters an inclusive culture where differences are celebrated to drive the best business decisions possible. We do not discriminate on any basis covered by appropriate law. All employment is decided on the consideration of merit, qualifications, need and performance.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As an Application Security Engineer, you will contribute to finding and responding to security vulnerabilities across the Brex platform. In this role, you will participate in code reviews, design reviews, penetration testing, and vulnerability management. You will contribute to tooling that performs static and dynamic testing of the Brex platform and supports secure developer workflows. Application Security is part of our wider Financial Scale organization, which means you will work closely with Security Operations, GRC, Product Security, Front End Platform, and IT Infrastructure teams.

We're looking for individuals with a solid foundation in penetration testing and a curiosity for finding vulnerabilities in complex systems. You should have experience identifying and documenting vulnerabilities across common vulnerability classes and be able to communicate their risk clearly to engineering and product teams. This role is highly cross-functional — you'll have the opportunity to collaborate with engineering teams across Brex and grow your security expertise in a fast-moving environment.

Brex is pioneering the next wave of AI-driven financial services for dynamic, high-impact companies like Coinbase, Robinhood, and Anthropic. As we integrate AI across our product suite, this role will give you hands-on experience contributing to AI security at Brex. You'll apply emerging AI security best practices to help secure our agentic features, identify attack surfaces introduced by LLM-powered systems, and partner with product and engineering teams to build AI capabilities our customers can trust with their critical financial operations.

Responsibilities

• Identify vulnerabilities across common vulnerability classes (e.g., OWASP Top 10), document findings clearly, and communicate risk to drive remediation efforts
• Participate in penetration testing and design reviews alongside senior engineers, contributing to the identification of vulnerabilities and insecure designs
• Contribute to internal tooling and automation efforts that support SAST and DAST testing of the Brex platform and promote secure development practices
• Collaborate with engineering and product teams to support the design of secure product features
• Actively contribute to a culture of security awareness through knowledge sharing and peer learning

Requirements

• 4+ years of work experience in Application Security or a related role
• Demonstrated ability to find and document vulnerabilities in complex systems, with clear communication of business risk
• Hands-on experience with a subset of secure development activities, such as code review, threat modeling, or penetration testing
• Experience identifying security risks in AI/ML systems — such as prompt injection, model manipulation, or data poisoning — through work experience, personal projects, CTFs, or bug bounties
• Familiarity with agentic workflows and the ability to reason about attack surfaces introduced by LLM-powered features
• Knowledge of Python or scripting languages to automate tasks and build tooling
• Collaborative mindset paired with strong written and verbal communication skills

Bonus points

• Experience with Kotlin, gRPC, GraphQL, Kubernetes
• Previous experience as a software engineer
• Experience with securing distributed systems in AWS and cloud environments
• Experience with web application security reviews
• Contributions to the wider technical community — open source, public research, CTF participation, blogging, CVEs, or presentations
• Experience submitting to bug bounty or responsible disclosure programs
• Published AI security research or contributions to AI security frameworks

Compensation

The expected salary range for this role is $152,000 - $190,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

CAIS is the pioneer in democratizing access to and education about alternative investments for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions. CAIS provides financial advisors with a broad selection of alternative investment strategies, including hedge funds, private equity, private credit, real estate, digital assets, and structured notes. CAIS also delivers industry-leading technology, operational efficiency, and world-class client service throughout the pre-trade, trade, and post-trade experience. CAIS supports over 50,000 advisors who oversee more than $6 trillion in network assets.

The AI-Forward IT Support Engineer is the visible face of IT at CAIS headquarters. This role owns the day-to-day support experience—managing the support team, serving as the senior escalation point, and making sure employees can get things done. Alongside that, this person is a genuine practitioner of AI tools, using them to manage, maintain, and engineer solutions in the Microsoft ecosystem.

The AI dimension here is practical and people-facing: comfort with tools like Claude and Codex, the ability to get employees access to what they need, and the enthusiasm to show someone how to write their first useful prompt. The goal is to be the person who makes AI feel accessible, not intimidating.

Key Responsibilties 

Pillar 1 — IT Support Leadership & Microsoft Estate

• Support Team Management: Manage CAIS’s support function firmwide, leveraging internal staff and MSP resources. Hold partners accountable for performance and drive continuous improvement in service quality.
• Senior Escalation Point: Act as the senior escalation point for all end-user support issues across the organization. Own complex or unresolved tickets through to resolution, ensuring no issue falls through the cracks between the support team and internal stakeholders.
• Microsoft Environment Management: Lead day-to-day administration and engineering of the CAIS Microsoft estate: Intune device policies and compliance profiles, Azure / Entra enterprise application management, and M365 service health. Beyond break-fix—this includes proactive configuration, policy improvement, and keeping the environment clean and well governed.
• Visible Face of IT: Be physically present and accessible at CAIS HQ. Build trust with employees as the go-to person when something isn’t working—whether that’s a support issue or a question about technology. Represent IT in a way that is responsive, human, and credible.

Pillar 2 — AI Operations & End-User Enablement

• AI Tooling Comfort: Use Claude Code and OpenAI Codex as primary tools for engineering solutions in the Microsoft environment—generating and refining scripts, automating repetitive admin tasks, troubleshooting configurations, and improving documentation. AI tooling is how this person works, not an afterthought.
• AI Access Operations: Ensure CAIS employees have access to the AI tools they need. Manage provisioning, permissions, and basic configuration for end-user AI platforms. Be the first point of contact when someone can’t get in, doesn’t know where to start, or needs a tool set up.
• On-Ramp & Evangelism: Help colleagues take their first steps with AI tooling. Run informal sessions, share practical tips, introduce basic prompt engineering concepts, and be available for one-on-one guidance. The goal is not deep training—it’s making the tools feel approachable and getting people to their first win as quickly as possible.

Required

• Experience managing a support function—internal team, MSP, offshore, or a combination; comfortable holding vendors and partners accountable to service standards
• Strong hands-on knowledge of Microsoft 365, Azure / Entra ID, and Intune—able to own configuration and policy work, not just administer tickets
• Comfortable daily user of Claude Code, OpenAI Codex, or equivalent AI tooling—applied to real engineering and administrative tasks
• Excellent communication and interpersonal skills—comfortable engaging at all levels of the organization and able to explain technology clearly to non-technical users in plain, practical terms

Preferred

• Financial services industry experience or a similar fast-paced, entrepreneurial environment

Qualifications

• 5+ years of progressive IT experience
• 2+ years leading a support function or small team
• Demonstrated experience using AI tools (e.g., Copilot, ChatGPT, Claude)
• Hands-on expertise in automating Microsoft 365, Azure, and Intune environments

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning systems and infrastructure
• Thrive in environments where technical excellence directly drives both business results and research breakthroughs
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP, Azure)
• Python or Rust

Representative projects:

• Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators
• Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
• Building production-grade deployment pipelines for releasing new models to millions of users
• Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
• Contributing to new inference features (e.g., structured sampling, prompt caching)
• Supporting inference for new model architectures
• Analyzing observability data to tune performance based on real-world production workloads
• Managing multi-region deployments and geographic routing for global customers

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Position Summary

Arcesium is seeking a Software Engineer to join our Forward Deployed (FD) team within Client and Partner Development. This role is distinct from traditional product engineering: our mission is time to value. Forward Deployed Engineers rapidly design and deliver solutions that directly address client business needs while building reusable foundations that make the next project faster and better.   

This role prioritizes autonomy, execution, and impact. You won’t be limited to incremental features on a fixed roadmap; you’ll help define the problems, shape the solutions, and deliver outcomes that matter to both clients and the product. Your work will power client relationships, accelerate adoption of Arcesium’s platform, and shape the evolution of our products. Forward Deployed Engineers sit in a uniquely leveraged position: seeing client problems first, solving them end-to-end, and turning those solutions into lasting capabilities for the platform.  

What Makes This Role Unique  

• Time-to-value is the mission.  Solutions must be delivered quickly while building strategic infrastructure that accelerates future work. 
• You work directly with clients.  FD Engineers are part of the face of Arcesium and partner closely with client technology owners and business stakeholders.  
• You close the loop with product.  You will identify patterns across client needs and translate them into improvements, features, and platform direction.  
• You build targeted, high-impact solutions.  Expect many small, self-contained deliverables that directly solve business problems alongside foundational components that endure.  
• Code lives at multiple horizons.  Some solutions run for years in production; others exist briefly to unlock immediate value.

Responsibilities

• Own execution and delivery of client-facing technical solutions, integrations, and data workflows. 
• Gather requirements, iterate on deliverables, and drive projects through completion with client technology owners, client executives, and Arcesium stakeholders. 
• Design and build data pipelines, integrations, and targeted applications that address specific business needs. 
• Collaborate with platform and product engineers on architecture, patterns, and reusable capabilities informed by client work. 
• Rapidly prototype and deliver proof-of-concepts that demonstrate value and inform longer-term solutions. 
• Contribute feedback and real-world use cases to product teams to influence roadmap and platform evolution. 
• Operate across environments: your solutions may run in Arcesium’s platform, client environments, or someone’s laptop. 

Qualifications

• 5+ years delivering data-centric technical solutions to enterprise-scale customers is preferred, but what we’re really looking for is someone with the drive to solve real problems on time, drive innovation, and make yourself and the people around you better every day. You will need to take ownership through ambiguity and connect technical work to business outcomes. If that sounds like you, come show us what you can do – we would love to have you. 
• Experience across software engineering, solution delivery, and client collaboration. 
• Strong programming skills. We use Java, Python, TypeScript, and SQL. 
• Ability to balance speed and quality, building both rapid solutions and durable systems. 
• Experience with cloud platforms and the modern data stack is a plus. 
• Familiarity with financial services, investment lifecycle, or asset management is a plus. 
• Experience using AI in enterprise products and systems, both internal and client-facing, is a plus. 

The expected annual base salary for this position is $200,000 - $240,000 Base. Our compensation package includes variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, benefits including medical and prescription drug coverage, and 401k contribution matching.

The applicable annual base salary paid to a successful applicant will be determined based on multiple factors including without limitation the nature and extent of prior experience and educational background.  #LI-JS1 #LI-Hybrid

Remote eligible states include: CA, CT, DE, FL, GA, IL, MA, MN, NJ, NY, NC, OH, PA, TX, VT, WA

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

Sovrn is a supply-side platform (SSP) built to help publishers grow, protect, and understand their businesses. We operate at the intersection of programmatic advertising infrastructure and publisher monetization — processing hundreds of billions of ad requests daily across a global, high-throughput exchange.

We're looking for a Principal Software Engineer with deep roots in adtech infrastructure and a genuine conviction about what AI-native engineering looks like in practice. This role is backend-focused at its core — you'll work on the systems that power our exchange, from bid request processing and traffic shaping to data pipelines and auction logic. But we're also at an inflection point in how we build software, and we want this person to help lead us through it.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Java, Kafka (Redpanda), AWS, Databricks, Datadog, ONYX.

What you'll be doing:

• Own the design and evolution of backend systems that operate at exchange scale — high throughput, low latency, always on
• Lead architectural decisions across auction infrastructure, bid processing, traffic shaping, and supply-side integrations
• Establish and champion AI engineering practices across the team — from prompt engineering and RAG patterns to agentic workflow design and LLM evaluation
• Identify high-leverage opportunities to apply AI in our adtech stack: traffic scoring and filtering, bid shading, yield optimization, anomaly detection, and automated decisioning
• Set standards for how we evaluate, trust, and operate AI-powered systems in production — including observability, fallback behavior, and model governance
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance

A successful candidate will have:

• 10+ years of software engineering experience, with a strong backend track record
• 5+ years working specifically in adtech infrastructure — SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Experience building and operating systems at exchange scale — high QPS, strict latency budgets, fault tolerance
• Demonstrated experience leading AI or agentic engineering efforts in production environments — not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Strong distributed systems fundamentals: messaging, caching, service architecture, observability
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn't the right tool — and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Hybrid #LI-Remote

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

Sovrn is a supply-side platform (SSP) built to help publishers grow, protect, and understand their businesses. We operate at the intersection of programmatic advertising infrastructure and publisher monetization — processing hundreds of billions of ad requests daily across a global, high-throughput exchange.

We’re looking for a Principal Software Engineer (Data) with deep roots in adtech data infrastructure and a genuine conviction about what AI-native data engineering looks like in practice. This is a specialized principal-level engineering role — one that carries all the architectural ownership and technical leadership expectations of a Principal Software Engineer, focused on Sovrn’s Data Collective.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Python, Pyspark, Kafka, Databricks, AWS

What you'll be doing:

Data Platform & Architecture

• Own the design and evolution of data platform systems that operate at exchange scale; high throughput, real-time streaming, and always-on batch pipelines
• Lead architectural decisions across data infrastructure: pipeline design, data modeling, lakehouse architecture, and data services layers
• Specify data platform components and configurations required for pipeline implementation; define pipeline observability to understand and improve performance at massive scale
• Research, implement, and evolve methods to process and democratize data across the organization
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end

AI & Agentic Engineering Leadership

• Establish and champion AI engineering practices across the team, from prompt engineering and RAG patterns to agentic workflow design, LLM evaluation, and progressive implementation of agentic design patterns
• Identify high-leverage opportunities to apply AI in our data stack: intelligent pipeline optimization, anomaly detection, automated data quality, forecasting, and LLM-powered data services
• Lead the evolution of our existing LLM and agentic tooling from passive use to intentional, well-architected integration within our data platform
• Set standards for how we evaluate, trust, and operate AI-powered systems in production, including observability, fallback behavior, and model governance
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it

Collaboration & Mentorship

• Provide domain expertise across the organization to enable business growth through data services and data models
• Provide counsel to all consumers and stakeholders of data to enable efficient and impactful use of our data assets
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance; foster a culture of innovation and continuous learning
• Operate with high autonomy across ambiguous, high-impact problems

A successful candidate will have:

• 10+ years of software engineering experience, with a strong data engineering and backend track record
• 5+ years working specifically in adtech data infrastructure, SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Excellent understanding of real-time streaming and batch pipelines, big data, and data lakes; hands-on experience in distributed data processing in the AWS ecosystem
• Strong understanding of second-layer big data platforms such as Snowflake and Databricks, applicable use cases, best practices, implementation, and support considerations
• Strong experience in structured, unstructured, and semi-structured data techniques; metadata management, data lineage, and data governance
• Experience with data security and compliance (PII, CCPA, GDPR, etc.)
• Demonstrated experience leading AI or agentic engineering efforts in production environments; not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, vector DBs, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Ability to clearly document and communicate architectural concepts at multiple levels; ability to lead problem definition, solution designs, and implementation work plans
• Understanding of DevOps and SRE practices
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn’t the right too, and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Remote, #LI-Hybrid

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

This is Engineering at Lattice

At Lattice, we build software that helps people and organizations thrive. Our engineering team values maintainable systems, strong collaboration, and thoughtful product experiences.

As we expand AI-powered capabilities across our platform, security is a core part of how we design, build, and operate our product. Our Product Security team partners closely with engineering to ensure we ship features that are secure by default and resilient in production.

What You Will Do

You will work closely with product and platform engineering teams to improve the security of Lattice’s applications and services.

Product Security & Engineering Partnership

• Partner with engineers to identify, triage, and remediate security issues in product features and services
• Participate in security reviews and threat modeling for new features and systems
• Perform security-focused code reviews and help identify common vulnerabilities
• Contribute to secure-by-default patterns, libraries, and tooling in our TypeScript-based stack

Security Tooling & Operations

• Help implement and operate security tooling (SAST, DAST, dependency scanning, etc.)
• Support vulnerability management workflows, including internal findings and bug bounty reports
• Assist in investigating security issues and assessing risk and impact

Cloud & Platform Security

• Collaborate with platform and infrastructure teams to improve application and cloud security posture
• Contribute to improving security practices in AWS-based environments

AI/LLM Security

• Assist in identifying and mitigating risks in AI/LLM-powered features, including prompt injection, data leakage, and unsafe output handling
• Apply emerging best practices (OWASP Top 10 for LLM Applications) to real product use cases

Security Enablement

• • Contribute to security guidance, documentation, and training for engineering teams
  • Help improve how security is integrated into the development lifecycle

What You Will Bring to the Table

Experience that is important for you to have at some level:

• 1–3+ years of experience in product security, application security, or software engineering
• Experience writing and maintaining code in JavaScript/TypeScript (or similar languages like Python or Ruby)
• Familiarity with common web and API vulnerabilities (e.g., OWASP Top 10)
• Exposure to security testing tools (SAST, DAST, dependency scanning, etc.)
• Experience working in or with cloud environments (AWS or similar)

Technical Approach

• Ability to identify common security risks and suggest practical mitigations
• Understanding of secure coding practices and basic security controls
• Interest in how security decisions impact real-world product systems

Collaboration & Growth

• Strong communication skills and ability to work closely with engineering teams
• Willingness to ask questions, learn quickly, and take ownership of well-scoped problems
• Ability to contribute to team discussions and share security context effectively

Experience that would be nice to have:

• Experience with modern web architectures (Next.js, NestJS, GraphQL)
• Familiarity with containerization or Kubernetes
• Experience or interest in AI/LLM security, including

Location Requirement:
This role is open to candidates located in British Columbia or Ontario, Canada. At this time, we are only able to hire employees residing in these provinces.

----

The estimated annual cash salary for this role is CAD $93,750 - CAD $125,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Life, AD&D, and Disability Insurance; Natural Disaster Support Program; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Working Remotely Stipend; One time WFH Office Set-Up Stipend; Retirement Plan; Financial Planning; and Learning & Development Budget.

*Note on Pay Transparency:

Lattice provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience.

Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

#LI-remote

Purpose of the role:

Working within Pico’s and Pico’s clients’ various Data Centers in New Jersey with some travel to Chicago, Mexico and Canada, the role holder will be responsible for the physical build and maintenance of our environment. Working closely with our Network and Systems engineering teams and our Project Management and client Service Delivery functions to ensure prompt delivery of all projects. With a structured approach, strong team ethos and the flexibility and commitment to solve problems and get things done, the role holder will be a key member of this small but highly skilled and integral team.  A key requirement of this job is flexibility as the role holder will be expected to work in short change windows, late at night and out of hours.

Responsibilities and duties (include but not limited to)

This includes, but is not limited to the following services:

• Equipment Rack and Stack
• Cable, Label & terminate fiber or copper network cabling
• Assist with the diagnosis of hardware and software - troubleshooting
• Perform cabinet/cage audits
• Blade/Card, Memory, Hard Drive, and Transceiver installations or removal
• Testing and troubleshooting of copper and fiber optic circuits
• Perform migrations of equipment, power, or networking devices
• Shipping and receiving packages in Office and co-locations
• Receive, log, and store internal packages
• Arrange access for internal and external customers
• Order, receive, install, and test cross connects (copper/fiber)
• Provide timely updates using a computer-based ticketing system
• Perform and document inventory verification/counts and rack elevation
• Monitor and report on power utilization in co-locations
• Maintain overall Data Centre cleanliness and appearance
• Work flexible shift schedules including rotational on-call coverage
• Report to the facility within a 1hour average for emergency outage assistance
• We operate many data centers across EMEA, the candidate will be required to travel throughout Europe, sometimes on very short notice, particularly in the short term.
• Home base will be the New Jersey area

Education, Skills and background (incl. Education and Experience Requirements)

• 5+ years of experience in Telecommunications or Data Centre related field
• In depth knowledge of Telecom structured cabling standards
• In depth knowledge of network device / server deployment
• In depth knowledge of DCO standards and operations
• 5+ years use of industry standard test equipment
• Effective organizational skills and high attention to detail
• Building Management System and Branch Circuit Monitoring experience
• Strong troubleshooting skills
• Professional business communication and interpersonal skills
• Mission Critical Data Centre Facility Maintenance

Working Arrangements

The working days for this role are Tuesday to Saturday: Tuesday to Friday 4 PM to midnight and Sat 9 AM to 5 PM. Sunday availability on request.   This is a non-office-based position. Travel between data centers in New Jersey (and occasionally beyond) will be required on an on-going basis. Home base is New Jersey, where we operate out of Equinix NY4, the travel is primarily within AMRS. The role holder will be expected to work whatever hours are necessary for the performance of this role (recognizing that it involves multiple jurisdictions / geographies including but not limited to EMEA, USA and APAC).

Other important information

Physical demands of the position include:

• Lift and handle up to 50 pounds
• Bend, stoop, and stretch as required for placement and retrieval of network devices, materials, or equipment
• Work under a raised data center floor
• Climb ladders (up to a16 feet) to reach plenum spaces

IMPORTANT DATA PRIVACY INFORMATION: 

This position is available with Pico Services Inc. The controller of your personal data will be Pico Services Inc.

For further information on what personal data we collect, how we will process your personal data and your rights with respect to your personal data please read our Pico Job Candidate Privacy Notice, View Here.

Project Overview

This is a cutting-edge initiative to integrate Large Language Models (LLMs) with WorldQuant's proprietary strategy management tools. The project aims to provide AI-assisted insights, automate routine analytical tasks, and enable natural language interactions for Portfolio Managers to more efficiently analyze, maintain, and enhance their trading strategies. This involves building foundational infrastructure, developing robust data pipelines for metrics and features, and creating a secure, user-centric interface with a strong focus on protecting intellectual property.

The Role:

We are seeking a talented and motivated Full-Time Software Engineer to play a key role in the development and enhancement of this AI-driven platform. You will be responsible for designing, building, and maintaining critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform. This includes enhancing existing MCPs, such as our proprietary command-line interface for strategy data, developing new MCPs for internal data system integration, strategy analysis, and performance metrics, and contributing to the secure and effective use of LLMs.

Key Responsibilities

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including our internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs, including but not limited to MCPs for direct data system integration, MCPs for strategy analytics, and MCPs for performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing the risk of intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between different systems (internal knowledge management systems, simulation systems, data warehouses).
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

What You’ll Bring:

Core Skills:

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding of or experience with prompt engineering principles for Large Language Models
• Awareness of data security and intellectual property protection considerations in the context of AI and LLM applications

Domain-Specific Knowledge (Highly Beneficial):

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms (familiarity with internal data systems or command-line data tools is a significant plus).

Technical Environment Familiarity (Helpful):

• Experience working in a Linux environment.
• Understanding of Command Line Interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to work effectively in a team.
• High attention to detail and commitment to delivering high-quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

Education

• Bachelor's or Master's degree in Computer Science, Engineering

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

AI is moving fast and Stripe is moving fast to adopt it. But we need to make sure we do all of this safely, and for most of these tools enterprise-grade security isn't just available off the shelf. That's where the AI security team comes in - we are responsible for building and partnering to create the right security primitives to enable Stripe to move fast safely.

This is a team that will be working in the low level components of our AI stack so both infrastructure and security experience are pluses. This space is moving fast so being comfortable with ambiguity and changes in priority are a must.

This is a foundational role — you'd be the first engineer on the team.

What you’ll do

Engineers on this team will do a mixture of partnering and advising with teams building AI infrastructure and products, and building security infrastructure primitives for AI. 

One of our major focuses will be building a security tooling layer that sits in the inference path, providing detection and protection against AI specific threats like prompt injection, jailbreaks, and tool misuse.

Responsibilities

• Build security frameworks integrated with our core AI infrastructure
• Design and implement defenses against AI specific threats like prompt injection and jailbreaks
• Collaborate with other engineering teams to ensure Stripe's AI infrastructure and products are built securely
• Support other engineering teams in integrating security primitives
• Uphold our high engineering standards and improve our codebase and processes
• Design and build systems that help define the state of the art for AI security

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of software development experience
• Experience independently designing and developing medium to large projects
• Experience working collaboratively across multiple engineering teams
• Experience writing high quality code in a major programming language
• Ability to drive clear next steps when working in an ambiguous environment
• Ability to think creatively and reason clearly in a complex problem domain

Preferred qualifications

• Experience developing, deploying, and maintaining reliable infrastructure systems
• Experience in security engineering
• Experience building AI agents or LLM-based systems

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform. We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users.

What you’ll do

As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently.

You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account.

Responsibilities

Our team operates fluidly and here are some problems you may tackle:

• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence.
• Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale.
• Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard.
• Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc.
• Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability.
• Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years in AI/ML and backend engineering.
• Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc.
• Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.

Preferred qualifications

• Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.
• Track record building ML platforms, especially those that enable multiple teams to collaborate together.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you.

Please note: This position is not eligible for immigration sponsorship. 

Company Overview

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark.

Principal Quality Automation Architect

The Principal Quality Automation Architect designs and scales Accordion's automated quality framework across products, services, and AI-enabled workflows. This impactful role will be critical in owning the architecture behind automated validation, test harnesses, evaluation pipelines, test data strategy, and cross-pod tooling standards.

This position will ideally be based in one of our US offices and is a hybrid role with the flexibility to work remotely 2 days per week (also eligible for remote candidates).

This position is not eligible for immigration sponsorship.

What You’ll Do:

Automation Architecture

• Design and implement the core automation framework for functional, API, integration, regression, and workflow testing
• Define standards for reusable test assets, environment usage, data setup, and evidence capture
• Create scalable approaches to testing complex, multi-system workflows

AI Evaluation Infrastructure

• Build and maintain regression harnesses for AI-enabled features, including prompt and workflow comparisons, scored evaluation runs, and benchmark execution
• Partner with AI quality analysts to support rubric-based testing and measurable release criteria

Test Data & Environment Strategy

• Define approaches for test data, synthetic data, masked data, and scenario generation
• Improve reliability and repeatability of validation environments

Engineering Partnership

• Work closely with software engineers to improve testability, observability, CI/CD integration, and defect prevention
• Help pods move quality checks earlier in the development lifecycle

You Have:

• 7+ years of experience in QA automation, SDET, or quality engineering roles, with a focus on scale, repeatability, and leverage
• Strong experience with test automation frameworks, API testing, CI/CD, and integration validation – you are systems-minded and deeply technical
• Strong scripting or coding skills
• Experience working with data-intensive or workflow-heavy applications
• Exposure to AI or LLM validation tooling or strong interest in building in that space
• Ability to design frameworks, not just individual tests, and comfortability setting standards that others adopt
• Commitment to balancing sophistication with delivery pace
• Bachelor's degree preferred

You Are:

• Excited to be part of a growing team, with a focus on driving future growth
• Passionate about delivering exceptional client service
• Knowledgeable about the relationship between Private Equity sponsors and their portfolio companies, particularly within the office of the CFO
• Willing to get your hands dirty in the details of a project while simultaneously seeing the whole picture
• Comfortable managing projects with multiple complex workstreams while also focused on your single workstream (you are managing and doing)
• A self-starter with a strong work ethic
• Full of entrepreneurial spirit and comfortable in a fluid, flat organization
• Able to effectively communicate complex issues and solutions, and raise issues to senior team members when necessary
• A team player, able to work with team members across all levels
• Someone who enjoys mentoring others and doing meaningful work
• A leader of others; you lead by example

The annual salary for this role ranges from: $150,000 to $190,000 + benefits + bonus.

Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity.

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law.

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.

#LI-HA1

About the role: 

Turing is looking for people with LLM experience to join us in solving business problems for our Fortune 500 customers. You will be a key member of the Turing GenAI delivery organization and part of  a GenAI project. You will be required to work with a team of other Turing engineers across different skill sets. In the past, the Turing GenAI delivery organization has implemented industry leading multi-agent LLM systems, RAG systems, and Open Source LLM deployments for major enterprises. 

Required skills

• 10–12+ years of professional, hands-on engineering experience, including 4–6+ years specializing in building and deploying AI/ML models and systems.
• 1+ years of experience in developing Generative AI (LLM) applications using techniques like prompt engineering, RAG, and/or agents.
• Expert in architecting GenAI applications/systems using various frameworks & cloud services
• Good proficiency in using various cloud services from Azure, GCP, or AWS for building the GenAI applications
• Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
• Experience in driving the engineering team toward a technical roadmap.
• Excellent communication skills to effectively collaborate with business SMEs

Roles & Responsibilities

• Build the technical roadmap given a business requirement and own the delivery of the same.
• Lead the engineering team toward a technical roadmap and ensure timely execution of the roadmap to achieve customer satisfaction. 
• Develop and optimize LLM-based solutions: Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
• Codebase ownership: Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
• Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
• Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
• Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
• Continuous innovation: Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.

Education

• Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related technical field.

Salary Range:$200-245K Base + equity

In 1600, William Gilbert published De Magnete—the first systematic study of magnetism. He didn't just theorize; he built instruments, ran experiments, and shared what he learned so that others could go further. Three centuries later, those foundations helped power the modern world.

At Mercury, we're making a deliberate, company-wide bet on AI. Frontier users are already pushing boundaries—building agents, automating workflows, moving fast. But they're doing it in silos. This role exists to change that: to take those scattered experiments and turn them into shared infrastructure, shared context, and shared capability. The goal is a multiplier effect—where the most ambitious AI work inside Mercury lifts the velocity of everyone else.

What you'll do

You'll join a team that has already started building Mercury's internal AI platform and enablement layer. Your work will be to extend, harden, and scale what's in motion, and to help partner teams adopt it.

Extend the AI platform foundation

• Build and evolve MCP servers that connect internal systems and data sources into a coherent interface for agents and engineers.
• Expand and operate our LLM gateway infrastructure: routing, rate limiting, cost attribution, and observability across teams.
• Turn early patterns into durable defaults: shared prompt libraries, guardrails, and policy-as-code so teams can move fast safely.

Strengthen the shared company knowledge layer

• Shape and maintain structured context artifacts—clean, reliable, agent-consumable—so LLMs working in Mercury's systems can reason accurately about our domain.
• Improve internal knowledge discoverability and retrieval so both humans and agents can quickly find accurate answers.
• Partner with domain teams to standardize key sources of truth, and keep them fresh.

Enable faster prototyping and iteration across the company

• Build and refine sandbox environments and tooling that let engineers experiment with AI safely and at speed.
• Create self-service scaffolding so non-engineers—PMs, ops, finance—can prototype and deploy AI-powered workflows with minimal hand-holding.
• Build playgrounds and evaluation harnesses so internal AI agents can be tested and iterated in controlled environments before hitting production.

This list is illustrative. Priorities will shift as we learn; the right person will help choose the next highest-leverage work.

The ideal candidate

• Has 5+ years of backend development experience in complex, production systems—you've built things that other engineers depended on.
• Is fluent across programming languages and can navigate platform engineering, infrastructure, and developer tooling without needing a map.
• Has hands-on experience building LLM-powered systems—RAG pipelines, agents, eval frameworks—and has shipped at least one of these to production.
• Understands the real tradeoffs in AI deployments: cost modeling, observability, latency, and safety—not just the exciting parts.
• Is high-agency and self-directed. You can operate effectively without tightly-defined scope, find the highest-leverage work, and get it done.
• Communicates clearly across technical and non-technical audiences—you can explain what you built and why it matters.

The total rewards package at Mercury includes base salary, equity, and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees (any location): $166,600 - $218,700
• Canadian employees (any location): CAD 157,400 - 206,650

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024. 

[Please see the independent bias audit report covering our use of Covey for more information.] 

#LI-ES1

What You’ll Do:

We are looking for an Applied AI Engineer to embed directly with our US commercial and operational teams building a human and agentic “operating system” that powers how we work as a company. In this role, you will be a builder and a problem-solver — someone who translates day-to-day operational pain points into practical AI agent and automation solutions that free up capacity for higher-value work.

This is an ideal role for someone who is passionate about applied AI, comfortable working across business and technical teams, and excited to see their work make an immediate and measurable impact.

Build & Deploy AI Agents and Automations

• Design, build, and deploy AI agents that automate administrative and repetitive workflows across commercial operations. 
• Identify high-value automation opportunities by working directly with stakeholders to map processes and surface inefficiencies.
• Develop solutions using LLMs (e.g., OpenAI, Anthropic Claude), workflow automation tools, RESTful APIs, and Python scripting.
• Prototype, iterate, and ship working solutions quickly — moving from problem to deployed tool with minimal overhead.

Partner with Business Teams

• Serve as the technical point of contact embedded within commercial and PMO teams, building strong working relationships with non-technical stakeholders.
• Translate ambiguous business needs into clear technical requirements and executable solutions.
• Communicate progress, surface blockers, and present solutions in a way that is accessible to both technical and non-technical audiences.

Maintain & Document

• Create and maintain clear technical documentation for all tools, workflows, and integrations you build.
• Monitor deployed solutions and proactively identify opportunities to improve reliability, performance, and adoption.

Who You Are

• Bachelors or Masters degree in Computer Science, Mathematics or Engineering
• Hands-on experience with AI/LLM tools, including configuring and prompting models from providers such as OpenAI or Anthropic (i.e. you’ve successfully shipped a product or feature using Claude Code)
• 2+ years of hands-on software development experience, including internships, co-ops, or personal projects with deployed, real-world applications
• Comfortable working with RESTful APIs, MCP servers, and integrating third-party services.
• Scripting language (i.e. Python) proficiency — you can write scripts, build lightweight automations, and debug independently.
• Understanding of prompt engineering best practices.
• Naturally curious and proactive — you seek out problems, propose solutions, and don’t wait to be told what to build next.
• Strong communicator who can work fluidly across business and engineering functions.
• Comfortable with ambiguity — you can scope your own work and adapt as priorities shift.
• Based in or able to work effectively within Eastern Time (EST).

DeepIntent is proud to offer a competitive compensation package inclusive of a base salary range of $110,000 -$150,000. The base salary range takes into consideration each candidates skills, experience and qualifications. In addition, we offer an annualized bonus plan and competitive benefits as well as many other company offerings.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

THE POSITION
Our roster has an opening with your name on it

We’re looking for passionate technologists, strong communicators, and those with a commitment to continuous improvement. The ideal candidate will have the confidence to propose pragmatic solutions to complex problems and be eager to learn from and educate others. As an AI software engineer, you will work in empowered, multidisciplinary teams, autonomously tackling complex challenges that provide the very best experiences and products for a growing community of millions of players as we build out an exciting and innovative customer experience within the fast paced and growing sports betting environment.

As a member of Tech Transformation team, you will research and build proof of concepts using new and innovative technologies to provide new and cutting-edge customer experiences and drive internal innovations for the business. You will be asked to think big and be willing to move fast. You’ll identify opportunities and put them into action quickly, and you won’t be afraid of to fail quickly.

When successful solution is identified, you’ll know how to build it for scale and longevity for our rapidly growing company. You write secure, stable, testable, maintainable code with minimal defects. You are proficient in a broad range of data structures and algorithms, knowing when it is appropriate to use them and when it is not. You make appropriate implementation trade-off decisions. You participate in team design, scoping, and prioritization discussions. You seek to learn the business context and technologies behind your team's software. You work effectively with other team members & identify any opportunities/problems arising from technical decisions. You invent, refine, and develop your solutions to ensure they are meeting customer needs and team goals. Most importantly, you are a passionate advocate for our customers.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• You rapidly prototype, experiment, and demonstrate production-like capabilities
• You work on project ideas and strategy with customers, stakeholders, and peers, balancing customer requirements with the team requirements, and strive to become a subject matter expert.
• You will always seek incremental delivery and you will pivot, when necessary
• You help lead your team when it comes to code quality and roadmap, by owning your team’s tech debt & tech improvement roadmaps.
• Drive engineering engagement best practices (e.g., Operational Excellence, Security, Quality, etc.) and set standards.
• Self-manage your craft by deliberately owning the outcome of key initiatives, delegating to and empowering teammates, pairing with your engineering manager to improve delivery, and proud to represent your team and Sportsbook.
• You foster a constructive dialogue and seek resolutions in a professional way.
• You keep yourself up to date with market standards and open-source frameworks.
• You provide excellent customer support on an on-call rotation where required.
• Most importantly, you are humble, pragmatic, self-managed, thirsty for knowledge, never satisfied and always challenging the norm.

THE STATS
What we're looking for in our next teammate

• BA/BS degree in Computer Science or related software engineering field, or equivalent practical experience. 7+ years of relevant work experience.
• Experience designing and delivering production-grade LLM/agent workflows, including tool/function calling, orchestration patterns, and retrieval-augmented generation (RAG), with clear strategies for prompt/version management, latency/cost controls, and reliability.
• Proven track record operationalizing LLM systems end-to-end, including automated evaluation (offline + online), telemetry/monitoring, guardrails, and incident response/playbooks to maintain quality over time
• Experience integrating LLM capabilities into existing services and SDLC, including CI/CD, testing strategies (unit/integration + LLM evals), and safe rollout patterns (feature flags, canaries, A/B tests)
• Experienced in exhibiting a very high standard of technical judgement, innovation and execution to tackle open-ended problems that require difficult prioritization, defining both the what and how of things to be done.
• Solid experience building and designing highly scalable, fault tolerant and always available systems
• Understanding of modern architectures, design patterns, and platform nuances
• Expertise in at least one higher level language (Pyhton, JS, Java, .NET)
• Fullstack experience owning building and designing highly scalable, fault tolerant and always available systems in React, React Native, Native and Node.JS backend.
• Strong experience helping lead software engineering teams across Web, Mobile, and/or connected devices spaces.
• Experience working with cloud-based infrastructure and technologies, preferably AWS
• Proficient in responsibility delegating, mentoring, and empowering individuals.
• Track record of owning the outcome of technical delivery.
• Passion for quality and understanding of quality best practices within an SDLC, with experience in unit testing, testing tools, or integrating testing.
• Strong sense of ownership, urgency, and drive with demonstrated abilities driving operational excellence and best practices.
• You’re passionate about the fast-paced, innovative, and growing Sports Betting industry.

ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.  

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, “We are One Team!”. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

The applicable salary range for this position is $170,000 - $213,000 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

#LI-Remote

The Role

We are seeking a Senior AI Engineer to join our AI Platform team. The AI Platform team is focused on enabling and building disruptive, innovative solutions to transform the wealth technology landscape with AI across our product suite and is growing quickly.

As a Senior AI Engineer, you will be responsible for architecting, leading, and driving the execution of the core AI capabilities that power our platform. This is a high-impact role for an engineer who thrives on the frontier of applied AI and maintains a relentless focus on shipping. You will not just work with LLMs and agentic frameworks; you will own the end-to-end delivery of AI-native products, ensuring that cutting-edge AI systems are hardened into robust, scalable, and high-performance production systems.

Addepar takes a market-based approach to pay. A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions.

The range displayed on each job posting reflects the minimum and maximum target base salary for roles in Colorado, California, and New York. The current range for this role is $179,000 - $224,000 (base salary) + bonus + equity + benefits.

Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits.

Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

What You’ll Do

• Drive the end-to-end execution and delivery of AI-native products, moving from initial prototype to scalable production services with high velocity.
• Architect, build, and productionize core components of our AI platform – including:
• LLMs and the surrounding ecosystem (e.g., vector DBs, prompt tuning, etc.)
• Agentic frameworks
• Core agent capabilities like MCP/ cross-platform tool use, web browsing, computer use
• Enforce technical discipline and operational excellence for all of our AI products.
• Rapidly iterate on AI products based on performance metrics and user feedback to drive continuous improvement.
• Lead the evaluation and adoption of new AI technologies and frameworks to keep Addepar on the frontier of the industry.
• Partner with product managers and other engineering teams to translate strategic goals into technical realities, abstracting AI complexity so they can iterate quickly.

Who You Are

• 3-6+ years of professional experience in backend software engineering, with expertise in programming languages/technologies like Python, Golang, gRPC, AWS, and Kubernetes.
• Proven track record of owning and shipping complex, production-grade systems.
• Proven experience shipping and maintaining AI-native products or features, or demonstrable passion through significant personal projects in AI.
• Deep ownership mindset, seeing projects through to completion and raising the bar for execution across the team.
• A strong bias for action, with a passion for shipping rapidly and iterating with feedback.
• BS/MS in Computer Science, Statistics, Mathematics, or another quantitative field, or equivalent experience.
• Bonus Points (Preferred Qualifications):
  • Specific experience with LLMs and agentic systems.
  • Hands-on experience with technologies in the modern AI/LLM ecosystem, such as Databricks, Langchain, or MLFlow.
  • Advanced understanding of the probabilistic systems underpinning modern LLMs.
  • Experience building AI products in highly accuracy-sensitive domains such as finance is a plus.

What You Will Do and Learn 

We are hiring an AI Training & Enablement Lead to drive firm-wide adoption of our AI platform and agentic tools. In this role, you are responsible for end-to-end execution, not just strategy. You will design, create, and deliver the training programs, enablement materials, release communications, and change management plans that help 700+ consultants integrate AI into their daily work. 

You will own the full lifecycle of user enablement: from onboarding new users, to managing release rollouts, to measuring adoption and identifying friction points. You’ll have access to support resources, while playing a leading role in building and delivering impactful solutions. 

In this role, you can expect to: 

Training Program Design & Delivery 

• Build and maintain role-based training curricula for different personas (consultants, architects, engagement leads, practice leaders) aligned to the AI platform's capabilities and governance requirements. 

• Create hands-on workshops, quick-start guides, video walkthroughs, prompt libraries, and reference materials that consultants can use in the flow of work. 

• Facilitate live training sessions (virtual and in-person) for platform onboarding, new feature releases, and advanced use-case enablement. 

• Develop and manage an internal certification or proficiency program to track and incentivize AI skill development. 

Release Management & User Enablement 

• Own the user-facing release process: coordinate with the AI platform vendor and internal technical teams to translate product updates into clear, actionable enablement content. 

• Manage release notes, feature announcements, and "what's new" communications for each platform update. 

• Build and maintain a centralized enablement hub (knowledge base, FAQ, resource library) that serves as the single source of truth for all AI-related guidance. 

• Establish feedback loops with end users to surface adoption blockers, training gaps, and feature requests. 

Change Management & Communications 

• Design and execute change management strategy for the AI platform rollout, including stakeholder mapping, resistance planning, and leadership alignment. 

• Draft internal communications (emails, Teams updates, town hall talking points) that build excitement and reduce friction around new AI capabilities. 

• Identify and activate AI Champions across practices to scale peer-to-peer learning and create organic adoption momentum. 

• Partner with practice leaders and HR to integrate AI enablement into performance reviews, career development, and onboarding for new hires. 

Adoption Measurement & Continuous Improvement 

• Define and track adoption KPIs: active user rates, feature utilization, training completion, satisfaction scores, and time-to-value metrics. 

• Conduct regular pulse surveys and user interviews to assess enablement effectiveness and identify areas for improvement. 

• Report adoption progress and risks to leadership on a regular cadence, providing actionable recommendations. 

• Continuously iterate on training content and delivery methods based on data and user feedback. 

Skills & Experience: 

Required 

• 5-8+ years of experience in training, enablement, change management, or L&D, with at least 2 years focused on technology or platform adoption. 

• Proven ability to design and build training programs from the ground up, including curriculum development, content creation, resource design, and hands-on delivery. 

• Strong facilitation skills: you are comfortable leading workshops for groups ranging from 10 to 200 people, both virtually and in person. 

• Proven ability to translate complex technical concepts into accessible, engaging content for non-technical audiences. 

• Outstanding written and verbal communication skills, with a proven ability to craft clear, concise internal communications that effectively engage audiences. 

• Experience working in professional services, consulting, or technology firms. 

• Comfortable working in fast-paced environments with evolving priorities, and able to navigate ambiguity without a predefined playbook. 

Preferred 

• Prior experience with change management frameworks (Prosci, ADKAR, or equivalent). Certification. 

• Hands-on experience with generative AI tools (ChatGPT, Claude, Copilot, or similar). You do not need to be an engineer, but you should be a confident, daily user. 

• Experience managing enablement for SaaS platform rollouts (Salesforce, Anaplan, ServiceNow, or similar enterprise tools). 

• Familiarity with instructional design principles and e-learning authoring tools (Articulate, Loom, Camtasia, or equivalent). 

• Background in or exposure to consulting delivery models, T&M billing, and the dynamics of utilization-based businesses. 

• Experience building and activating champion or ambassador networks within large organizations. 

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role

AlphaSense is seeking an experienced engineering leader to transform how we build and operate AI-powered systems at scale. You'll join a team of brilliant engineers who've built cutting-edge AI applications, and your mission will be to bring world-class engineering practices that ensure these innovations run reliably for our enterprise customers.

This is a unique opportunity for a seasoned engineer who thrives on building robust platforms, mentoring talented teams, and establishing engineering excellence. You'll have significant autonomy to shape our technical architecture while working with frontier AI models and agentic systems that power market intelligence for the world's leading companies.

What You'll Do

• Architect for Scale: Design and implement distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency
• Build Engineering Excellence: Establish comprehensive testing strategies, observability systems, and CI/CD pipelines that catch issues before customers do
• Lead Through Expertise: Mentor a team of smart, motivated engineers, sharing your experience in building production systems that don't break at 3 AM
• Drive Platform Evolution: Own the technical roadmap for our AI platform, making architectural decisions that will shape our systems for years to come
• Bridge AI and Engineering: Collaborate with ML engineers and researchers to productionize cutting-edge AI capabilities while maintaining system stability

What We're Looking For

Required:

• 7+ years building and operating distributed systems in production
• Track record of improving system reliability (taking services from frequent outages to 99.9%+ uptime)
• Deep expertise in modern engineering practices: microservices, containerization (Kubernetes), infrastructure as code
• Experience leading technical initiatives and mentoring engineering teams
• Strong coding skills with ability to work across the stack
• Excellence in debugging production issues and implementing comprehensive observability
• History of making pragmatic trade-offs between perfect and shipped

Preferred:

• Experience with LLM applications, agent frameworks, or AI/ML infrastructure
• Familiarity with prompt engineering, RAG patterns, vector databases
• Background at high-growth companies or modern engineering cultures
• Experience with multi-model AI systems (OpenAI, Anthropic, Google, etc.)

Impact You'll Have

Within your first year, you'll transform how we build and operate software. You'll reduce incidents, establish testing and observability standards that become part of our DNA, and build platforms that enable other engineers to ship faster and safer. Most importantly, you'll elevate an entire team of engineers, sharing the expertise that only comes from years of building systems at scale.

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role

AlphaSense is seeking an experienced engineering leader to transform how we build and operate AI-powered systems at scale. You'll join a team of brilliant engineers who've built cutting-edge AI applications, and your mission will be to bring world-class engineering practices that ensure these innovations run reliably for our enterprise customers.

This is a unique opportunity for a seasoned engineer who thrives on building robust platforms, mentoring talented teams, and establishing engineering excellence. You'll have significant autonomy to shape our technical architecture while working with frontier AI models and agentic systems that power market intelligence for the world's leading companies.

What You'll Do

• Architect for Scale: Design and implement distributed systems that power AI agents processing thousands of requests per hour, ensuring reliability, performance, and cost-efficiency
• Build Engineering Excellence: Establish comprehensive testing strategies, observability systems, and CI/CD pipelines that catch issues before customers do
• Lead Through Expertise: Mentor a team of smart, motivated engineers, sharing your experience in building production systems that don't break at 3 AM
• Drive Platform Evolution: Own the technical roadmap for our AI platform, making architectural decisions that will shape our systems for years to come
• Bridge AI and Engineering: Collaborate with ML engineers and researchers to productionize cutting-edge AI capabilities while maintaining system stability

What We're Looking For

Required:

• 7+ years building and operating distributed systems in production
• Track record of improving system reliability (taking services from frequent outages to 99.9%+ uptime)
• Deep expertise in modern engineering practices: microservices, containerization (Kubernetes), infrastructure as code
• Experience leading technical initiatives and mentoring engineering teams
• Strong coding skills with ability to work across the stack
• Excellence in debugging production issues and implementing comprehensive observability
• History of making pragmatic trade-offs between perfect and shipped

Preferred:

• Experience with LLM applications, agent frameworks, or AI/ML infrastructure
• Familiarity with prompt engineering, RAG patterns, vector databases
• Background at high-growth companies or modern engineering cultures
• Experience with multi-model AI systems (OpenAI, Anthropic, Google, etc.)

Impact You'll Have

Within your first year, you'll transform how we build and operate software. You'll reduce incidents, establish testing and observability standards that become part of our DNA, and build platforms that enable other engineers to ship faster and safer. Most importantly, you'll elevate an entire team of engineers, sharing the expertise that only comes from years of building systems at scale.

The Opportunity

Good Inside is seeking a Senior Machine Learning Engineer to join our Engineering team. This is not a research or data science role – we’re looking for a strong backend engineer who has hands-on experience shipping ML-powered features in production. You’ll work at the intersection of backend systems and machine learning, building the infrastructure and services that bring personalized, intelligent experiences to our users.

You should be comfortable working with ML APIs, understanding core ML concepts, and integrating models into reliable, scalable backend systems. Your primary identity is as a software engineer – someone who writes clean, production-grade code – with the added ability to reason about ML systems and bring them to life in our product.

You will collaborate closely with cross-functional partners, including product, design, mobile, and data teams, to build high-quality features that serve our users’ needs. Your ability to blend backend engineering excellence with practical ML knowledge will be essential as we continue to evolve and scale the Good Inside platform.

This role follows a hybrid schedule, with three in-office days each week at our Manhattan location.

What You’ll Own

• Design, build, and maintain backend services and APIs that power ML-driven features across the Good Inside platform
• Integrate and orchestrate ML models and third-party ML APIs (e.g., LLM providers, recommendation engines, embeddings services) into production systems
• Build data pipelines and infrastructure to support model serving, feature storage, and real-time personalization
• Collaborate closely with product, mobile, and design teams to translate ML capabilities into user-facing features
• Own the reliability, performance, and scalability of ML-adjacent backend systems
• Develop clean, maintainable, and well-documented code aligned with defined project scope
• Provide clear documentation of architectural decisions, implementation details, and handoff materials upon project completion
• Provide input on feature scope and sequencing to support timely and successful delivery of project deliverables

Your Skills and Experience

• 5+ years of professional software engineering experience, with a strong focus on backend development
• Demonstrated experience shipping ML-powered features or products in a production environment
• Working knowledge of ML concepts (e.g., embeddings, classification, recommendation systems, LLMs) – you don’t need to train models, but you need to understand how they work and when to use them
• Hands-on experience integrating ML APIs and services (e.g., OpenAI, Anthropic, ElevenLabs, HuggingFace, AWS SageMaker, or similar)
• Proficiency in Python and/or another backend language (Go, Java, TypeScript/Node, etc.)
• Experience with cloud infrastructure (AWS, GCP, or Azure) and containerized deployments
• Familiarity with data stores and pipelines relevant to ML workloads (e.g., vector databases, feature stores, streaming systems)
• Excellent interpersonal, verbal, and written communication skills
• Strong collaboration abilities and cross-functional relationship-building
• Self-starter with strong analytical and problem-solving skills
• Ability to stay organized and deliver results in a fast-paced, changing environment
• Computer Science degree or equivalent
• At least 2 years of experience in house as a ML Engineer 

Preferred Experience

• Startup Growth Experience: This isn’t your first time helping a high-growth startup scale. You are excited by the challenge and love creating and learning from the bottom up.
• Experience with LLM Application Development: You’ve built applications on top of large language models – prompt engineering, RAG pipelines, conversational AI, or similar – and understand the practical challenges of shipping LLM-powered features.
• Infrastructure & DevOps Fluency: Experience with CI/CD, monitoring, observability, and production-readiness for ML systems.
• Prior experience with recommendation systems, personalization engines, or content ranking algorithms in a user-facing product.

What We Offer

• Competitive Compensation: base salary for this role will be $205k - $235k 
• Company Equity
• Comprehensive benefits package
• 401k + Company match
• Time off to recharge
• Hybrid work environment
• A high-ownership, high-performance, high-collaboration culture