Recorded Future provides intelligence that 1,500+ clients use to defend their people and networks from cybersecurity threats. Our intelligence data provides analytics for many security and risk management needs. This data is derived from technical data, threat actor monitoring, social media, open sources, and other data sources. In this role, your mission is to design, build, and deploy the next generation of AI Agentic systems that process and enrich this intelligence data autonomously.

In this Senior Software Engineer role, you will be a key individual contributor, driving the development of resilient, scalable software systems focused on leveraging Large Language Models (LLMs) and autonomous agents for data processing, analysis, and threat detection. You will be responsible for building sophisticated, production-grade applications that enrich our threat intelligence, and you will mentor junior engineers, fostering technical excellence and best practices.

What You’ll Do:

• Design, develop, and deploy highly reliable and scalable software systems, specializing in AI Agentic tooling and ML applications.
• Serve as a technical leader in the implementation of frameworks and best practices for creating, evaluating, and safely deploying autonomous AI agents in a production environment.
• Collaborate with engineering managers and cross-functional teams to integrate AI Agent solutions across the platform.
• Drive engineering excellence by conducting rigorous code reviews, focusing on code quality, performance optimization, and operational maturity.
• Lead the technical design and architectural discussions for new features and components within the AI Tooling roadmap.
• Manage project tasks through an agile SDLC, ensuring timely delivery and high-quality results.

What You’ll Bring:

• Strong technical background in software engineering, with deep expertise in building and scaling distributed systems.
• Expert-level proficiency in Python and related ecosystem for production AI/ML applications.
• Proven track record as a senior individual contributor, designing and delivering complex software solutions.
• Technical skills with modern cloud platforms (e.g., AWS, GCP, Azure) and engineering workflow tools (e.g., Jira, Git).
• Deep understanding of the AI Agent paradigm, including hands-on experience with LLMs, prompt engineering, agentic loop design, and retrieval-augmented generation (RAG).
• Experience driving coordinated action between cross-functional teams (product, research, stakeholders) working from different locations around the world.
• A pragmatic mindset and a strong focus on delivering measurable, high-impact results.
• A keen curiosity for cybersecurity and finding innovative ways to apply AI Agent technology to keep our clients safe.

The base salary range for this full-time position is $129,000- $193,500. Our salary ranges are determined by role, level, and location. The salary displayed reflects the range for new hire salaries for the position across all US locations. Within the range, individual pay is determined by state, work location and additional factors, including job-related skills, experience, and relevant education or training. This position may be eligible for incentive compensation, equity, and medical, dental, vision, life insurance and 401K. Your recruiter can share more about the specific details of the compensation and benefit package during the hiring process.

#LI-Remote

Recorded Future provides intelligence that 1,500+ clients use to defend their people and networks from cybersecurity threats. Our intelligence data provides analytics for many security and risk management needs. This data is derived from technical data, threat actor monitoring, social media, open sources, and other data sources. In this role, your mission is to design, build, and deploy the next generation of AI Agentic systems that process and enrich this intelligence data autonomously.

In this Senior Software Engineer role, you will be a key individual contributor, driving the development of resilient, scalable software systems focused on leveraging Large Language Models (LLMs) and autonomous agents for data processing, analysis, and threat detection. You will be responsible for building sophisticated, production-grade applications that enrich our threat intelligence, and you will mentor junior engineers, fostering technical excellence and best practices.

What You’ll Do:

• Design, develop, and deploy highly reliable and scalable software systems, specializing in AI Agentic tooling and ML applications.
• Serve as a technical leader in the implementation of frameworks and best practices for creating, evaluating, and safely deploying autonomous AI agents in a production environment.
• Collaborate with engineering managers and cross-functional teams to integrate AI Agent solutions across the platform.
• Drive engineering excellence by conducting rigorous code reviews, focusing on code quality, performance optimization, and operational maturity.
• Lead the technical design and architectural discussions for new features and components within the AI Tooling roadmap.
• Manage project tasks through an agile SDLC, ensuring timely delivery and high-quality results.

What You’ll Bring:

• Strong technical background in software engineering, with deep expertise in building and scaling distributed systems.
• Expert-level proficiency in Python and related ecosystem for production AI/ML applications.
• Proven track record as a senior individual contributor, designing and delivering complex software solutions.
• Technical skills with modern cloud platforms (e.g., AWS, GCP, Azure) and engineering workflow tools (e.g., Jira, Git).
• Deep understanding of the AI Agent paradigm, including hands-on experience with LLMs, prompt engineering, agentic loop design, and retrieval-augmented generation (RAG).
• Experience driving coordinated action between cross-functional teams (product, research, stakeholders) working from different locations around the world.
• A pragmatic mindset and a strong focus on delivering measurable, high-impact results.
• A keen curiosity for cybersecurity and finding innovative ways to apply AI Agent technology to keep our clients safe.

The base salary range for this full-time position is $129,000- $193,500. Our salary ranges are determined by role, level, and location. The salary displayed reflects the range for new hire salaries for the position across all US locations. Within the range, individual pay is determined by state, work location and additional factors, including job-related skills, experience, and relevant education or training. This position may be eligible for incentive compensation, equity, and medical, dental, vision, life insurance and 401K. Your recruiter can share more about the specific details of the compensation and benefit package during the hiring process.

#LI-Remote

The Role

Fusion is a global electronics distributor building a modern data platform on top of a 20 year old legacy system. Palantir Foundry is a core part of that stack. We use it to deliver unified views of our customers, products, and operations, and we are leaning hard into AIP and agent driven workflows to compress delivery cycles. We are looking for a senior engineer who can work hands on in Foundry: building pipelines, ontology models, agents, and applications alongside our external Palantir consultants today, and progressively taking ownership as the platform matures.

This is an execution focused role with real autonomy. You will design and build solutions, work directly with business stakeholders, and have a voice in how the platform evolves.

What You’ll Do

• Build and maintain data pipelines: Design, build, and optimize batch and streaming pipelines in Foundry (Pipeline Builder with AI assist, Code Repositories, Code Workbook) that ingest data from internal and external source systems.
• Develop ontology models: Create and maintain ontology objects, relationships, link types, functions, and actions that represent business domains and power downstream applications, agents, and AIP workflows.
• Build AI native experiences with AIP: Use AIP Logic to compose AI driven functions, AIP Agent Studio to stand up domain agents, and AIP Threads or AIP Assist to embed conversational interfaces into Workshop apps. Use AIP Evals to validate prompt and agent behavior before promotion to production.
• Leverage AIP Analyst and FDE AI for delivery acceleration: Use AIP Analyst for ad hoc analytical work directly against the ontology, and lean on FDE AI and Solution Designer to scaffold ontology objects, pipelines, and starter applications. Refine the AI generated output, harden it for production, and bring it under proper change control.
• Deliver Foundry applications: Build and iterate on Workshop, Quiver, and Contour applications that give sales, operations, and leadership actionable views of the business, including embedded agentic actions and write back through Ontology Actions.
• Work alongside external consultants: Collaborate closely with our Palantir implementation partners to understand existing designs, validate data flows, and progressively take on more of the day to day Foundry work.
• Connect Foundry to the broader data platform: As the data modernization team builds out medallion layer domain stores and DBT based pipelines on Azure, help align Foundry’s ontology and ingestion paths so the platform can transition from legacy sources to the new architecture cleanly.
• Integrate with external systems: Build and maintain OSDK based integrations and APIs that connect Foundry to internal services and third party platforms.
• Engage stakeholders directly: Gather requirements from business teams, demo solutions, train end users, and incorporate feedback into iterations.
• Ensure data quality and observability: Implement validation, lineage tracking, health checks, and monitoring within Foundry pipelines. Build automated data quality checks, including AIP assisted ones, to keep data accurate and reliable.
• Apply AI tooling to your own workflow: Use AIP and AI assisted development practices to accelerate pipeline work, code review, and documentation.

What You Bring

Data Engineering Foundations

These are the bedrock skills we expect every senior data engineer on this team to have, regardless of platform. Foundry is the surface; these are the muscles underneath.

• 7+ years building production data pipelines in modern stacks.
• Strong SQL, including window functions, CTEs, set operations, and query optimization on large datasets. You can read an execution plan and explain the cost.
• Solid grasp of dimensional modeling (Kimball, star schema), Data Vault, or equivalent. You can defend a modeling choice with reasoning, not dogma.
• Experience designing for slowly changing dimensions, idempotent loads, late arriving data, backfills, and incremental processing.
• Proficiency in Python, including PySpark and pandas for transformation work.
• Working knowledge of the Spark execution model: partitioning, shuffles, skew, broadcast joins, and tuning.
• Experience with ETL and ELT patterns, CDC pipelines, and workflow orchestration.
• Familiarity with modern transformation frameworks such as DBT, including tests, documentation, snapshots, and incremental materializations.
• Understanding of columnar formats (Parquet, Delta, Iceberg), table formats, and partitioning strategies.
• Practical experience implementing data quality frameworks, data contracts, and SLAs between producers and consumers.
• Comfort with Git workflows, code review, branching strategies, and CI/CD for data platforms.

Palantir Foundry and AIP

• 2+ years hands on Palantir Foundry experience with delivered work you can describe in detail.
• Strong knowledge of core Foundry capabilities: Ontology Manager, Ontology Functions and Actions, Pipeline Builder, Code Repositories, Code Workbook, Workshop, Builds, and platform security (branching, resource allocation, rollbacks).
• Experience with Foundry analytical and integration tools: Quiver, Contour, OSDK, and Marketplace products.
• Hands on experience with AIP for augmenting data workflows: AIP Logic, AIP Assist and Threads, and AIP assisted Pipeline Builder.
• Familiarity with newer AIP surfaces is a strong plus: AIP Agent Studio, AIP Analyst, FDE AI and Solution Designer, AIP Evals, and Automate.
• Understanding of how to evaluate, guardrail, and version AI driven functions and agents in a production context.

Cloud, Architecture, and Stakeholder Skills

• Proficiency with Azure data services, or equivalent depth in AWS or GCP with willingness to work in Azure.
• Solid understanding of data modeling across relational, analytical, and document paradigms.
• Ability to translate business requirements into technical designs and explain trade offs to non technical stakeholders.
• Self directed work style. You identify what needs doing and get it done without waiting for direction.

Nice to Have

• Production experience with DBT on Azure (Synapse, Fabric, or Databricks).
• Experience with medallion architecture (Bronze, Silver, Gold) or lakehouse patterns on Databricks, Snowflake, or equivalent.
• Experience evaluating LLM powered features: prompt design, eval harnesses, hallucination guardrails, and cost or latency tuning.
• Experience building or operating real time pricing, recommendation, or scoring engines.
• Familiarity with electronics distribution, supply chain, or ERP data, particularly Dynamics GP and Great Plains.
• Background in domain driven design or microservices architecture.
• TypeScript or C# for OSDK consumers and downstream services.
• Exposure to CRM, payment, or logistics API integrations.

Why Fusion

• Greenfield meets legacy: You’ll help build a modern data platform while keeping a 20 year business running. Real engineering problems, not toy projects.
• Real impact, small team: A lean team where your work is visible and your judgment matters. No layers of approval.
• AI first engineering culture: We use AIP and AI tooling aggressively. One engineer with the right tools does the work of three.
• Global scale: Fusion operates across the US, Singapore, and Hong Kong. The platform serves users worldwide.

Paperless Parts provides the manufacturing industry with a SaaS platform that empowers the next generation of manufacturers to join the digital age. When manufacturers use our product, they free up valuable time for faster quoting and estimating, leading to increased profitability and reduced manual steps. From life-saving medical devices to critical components that unlock new depths of outer space, our customers produce parts that go into some of the world’s coolest and most impactful products. It is our mission to enable manufacturers with the technology they need to drive innovation forward.

We are a team of motivated and hardworking creators and doers. If you’re looking to have a direct impact on a Series B fast-scaling company that is revolutionizing an essential industry, read on and apply!

This is a full-time hybrid position based in Boston, MA.

This position requires activities that are subject to US Export Control Laws and require US Citizenship or Green Card Holder.

About the Role 

Step into the role of Principal Software Engineer and serve as a technical force multiplier for our engineering organization. In this high-leverage position, you will look beyond the immediate roadmap to define the architectural vision that will support Paperless Parts for years to come. You will bridge the gap between business strategy and technical execution, ensuring our systems are robust, scalable, and AI-ready.

This role is a powerful catalyst for change and innovation. You will be responsible for modernizing our engineering practices—integrating AI agents into the development lifecycle, driving the evolution from monolithic to a service architecture, and mentoring our engineers to become the next generation of leaders.

Who You Are

• Technical Visionary & Pragmatist: You have a proven track record of evolving complex architectures in scale-up environments. You balance the pursuit of "technical purity" with business reality, making hard trade-offs with incomplete information.
• Force Multiplier: You don't just write great code; you make the entire team better. You are passionate about mentorship and teaching others effective patterns for design, review, and agentic coding.
• AI Pioneer: You think strategically about how AI agents and workflows can fundamentally change how we build software. You believe that "what is good for humans is good for AI," championing standards that serve both.
• Business Partner: You understand that technical debt is a business risk. You can translate complex infrastructure needs into tangible business value (ROI, reliability, speed) to help leadership prioritize effectively.

Why You'll Love Working Here

• Architectural Authority: You will lead the design of our most critical systems, making high-stakes decisions on migrating to distributed architectures and defining our data strategy.
• Optimizing the AI-Native Workflow: You will have the freedom to operationalize AI at scale—implementing agents for ticket resolution, automated reviews, and documentation—driving significant improvements in modern engineering efficiency.
• High-Impact Work: Our software is used in mission-critical industries like aerospace and defense. The reliability and performance standards you set directly impact the production of life-saving and critical components.
• Culture of Excellence: You will help establish a culture of deep observability and operational maturity, leading the charge on incident management and blameless postmortems.

What You'll Do

• Architect & Evolve: Lead the technical strategy for migrating legacy monolithic patterns to scalable, service architectures. You will define the long-term vision for our backend systems, APIs, and cloud infrastructure.
• Operationalize AI Development: Drive the adoption and continuous improvement of AI-assisted workflows (using tools like Cursor and Claude Code). You will champion the strategic integration of AI agents to enhance autonomous task execution and leverage AI throughout the software life cycle.
• Drive Operational Maturity: Instill a strong focus on reliability and site operations across the team. You will lead initiatives to improve observability (logging, monitoring), define clear runbooks, and facilitate postmortems that turn incidents into structural improvements.
• Elevate Engineering Standards: Enforce "context-first" engineering. You will champion the creation of Architectural Decision Records (ADRs) and high-quality documentation, ensuring our codebase provides the explicit context needed for both human alignment and effective AI agent performance.
• Mentor & Lead: Act as a technical beacon, dedicating significant time (~20%) to pairing, design reviews, and mentoring engineers across different levels to elevate the team's collective skill set.
• Strategic Alignment: Collaborate with R&D leadership to prioritize technical initiatives. You will articulate the ROI of infrastructure investments and technical debt reduction in terms of customer reliability and business agility.

What You'll Bring

• 12+ years of experience in software engineering, with a strong background in architecting SaaS products at scale (start-up to scale-up transition experience preferred).
• Deep Architectural Expertise: Proven success decomposing monoliths and designing distributed systems, with strong judgment on build-vs-buy decisions and technology selection.
• Modern Stack Proficiency: Expert-level knowledge of modern web frameworks and databases, along with deep experience in AWS cloud-native patterns (containers, serverless).
• AI/LLM Fluency: Practical experience leveraging LLMs and AI agents in a production engineering workflow. You understand prompt engineering, context limits, and how to structure codebases for AI interpretability.
• Operational Rigor: A strong commitment to production reliability, with experience designing systems for observability and leading incident response processes.
• Communication Mastery: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and influence decisions without relying on authority.

Why Join Us?

• Impactful Work: Your contributions will power industries critical to our society and economy, making a real difference.
• Continuous Learning: We invest in our people and offer opportunities to learn, grow, and advance their careers.
• Supportive Culture: Our team is our greatest asset, and we foster an environment where everyone can thrive.

If you’re a forward-thinking engineer eager to make a significant impact while working with a talented, driven team, we’d love to hear from you!

Salary range:  $212,000 - $286,000

Location: Waltham, MA (hybrid- 3 days In-Office)

ERGO NEXT’s mission is to help entrepreneurs thrive. We’re doing that by building the only technology-led, full-stack provider of small business insurance in the industry, taking on the entire value chain and transforming the customer experience. 

Simply put, wherever you find small businesses, you’ll find ERGO NEXT.

Since 2016, we’ve helped hundreds of thousands of small business customers across the United States get fast, customized and affordable coverage. We’re backed by industry leaders in insurance and tech, and we still have room to grow — that’s where you come in.

What You’ll Do

• Design, implement, and optimize backend services that power machine learning-driven features in production environments
• Design and build backend systems that serve machine learning models in production, with a focus on performance, reliability, and scalability
• Ensure model predictions are observable and measurable, enabling evaluation using metrics such as precision, recall, and business impact
• Collaborate with product and cross-functional teams to refine requirements, prioritize high-impact problems, and translate them into clear technical solutions
• Contribute to system design, architecture reviews, and code quality improvements
• Diagnose and resolve complex issues across backend services, data pipelines, and model inference systems, including identifying gaps in model performance and system behavior
• Support innovation and continuous improvement by identifying opportunities and driving technical initiatives

What We Need

• 5+ years of backend engineering experience in Python
• Proven experience building high-performance or distributed systems
• Experience deploying and serving machine learning models in production systems, including building inference pipelines and integrating model outputs into backend services
• Experience evaluating model performance using metrics such as precision, recall, or other business-relevant measures
• Strong understanding of cloud infrastructure, microservices, and observability, including logging and monitoring systems to track model predictions and system performance
• Ability to operate effectively under ambiguity and navigate dynamic environments
• Strong communication and collaboration skills

This role focuses on building and operating production systems that leverage machine learning models. It is not primarily focused on model research, experimentation-only workflows, or prompt engineering.

We are hiring for multiple AI Engineers. US annual base salary ranges for this full time position are as follows:

• AI Engineer (IC1): 2+ Years of Experience: $105,000-$142,000
• AI Engineer (IC2): 3+ Years of Experience: $127,000-$171,000
• AI Engineer (IC3): 4+ Years of Experience: $152,000-$206,000

About Klaviyo

Klaviyo empowers creators to own their destiny by making first-party data accessible and actionable like never before. We see innovators building incredible businesses every day using Klaviyo's platform, and we're here to make sure they have everything they need to succeed. We're a company that puts customers first, leads with curiosity, and builds with velocity.

We're looking for people who are excited about solving hard problems, who thrive in a fast-paced environment, and who want to make a meaningful impact on how businesses grow.

About the Role

We're looking for a Director of Security Risk and Trust who breaks the mold of traditional compliance leadership. This isn't a role where you'll spend your days pushing spreadsheets and chasing attestation deadlines—this is a role where you'll engineer solutions to governance and compliance challenges at scale, build systems that make security and trust a competitive advantage, and lead a team that operates at the intersection of security engineering, risk management, and regulatory compliance.

You'll own the strategy and execution of Klaviyo's Risk and Trust program, partnering deeply with Engineering, Product, Legal, IT, and business teams to embed compliance and risk management into how we build and operate—not bolt it on after the fact. You'll bring a strong technical foundation and an engineering mindset to everything you do, from designing automated compliance pipelines to developing governance frameworks for AI/ML systems. You'll need to be as comfortable reading Terraform configs and reviewing architecture diagrams as you are presenting risk posture to executive leadership.

This role reports to the CISO and is a critical member of the Security leadership team.

How You'll Make a Difference

Build and Own the Risk and Trust Strategy

• Define and execute a forward-looking strategy that scales with Klaviyo's growth, product evolution, and expansion into new markets and regulated industries
• Develop a risk management program that quantifies and communicates risk in terms the business can act on—not just heat maps, but data-driven models that inform real decisions
• Own the compliance roadmap across frameworks including ISO 27001, ISO 42001, ISO 27017, ISO 27018, SOC 2 Type II, HIPAA, GDPR, CCPA/CPRA, and emerging AI governance regulations, identifying where frameworks overlap and engineering unified control sets rather than duplicating effort
• Translate regulatory and compliance requirements into clear, actionable engineering requirements that development teams can implement without ambiguity

Engineer Solutions, Don't Just Document Them

• Build and maintain compliance-as-code infrastructure—automated evidence collection, continuous control monitoring, and policy-as-code implementations that reduce manual toil and increase assurance
• Design and implement tooling and integrations (leveraging APIs, scripting, and orchestration platforms) that connect GRC workflows with engineering systems (CI/CD pipelines, cloud infrastructure, identity platforms, etc.)
• Partner with Engineering and Platform teams to embed security and compliance controls directly into the software development lifecycle, infrastructure provisioning, and deployment pipelines without introducing toil or friction
• Evaluate, select, and optimize platforms and technologies, building automation that turns compliance from a periodic exercise into a continuous, real-time capability

Lead AI Security Governance

• Develop and implement a comprehensive AI/ML governance framework aligned with ISO 42001, the EU AI Act, NIST AI RMF, and emerging global AI regulations
• Partner with ML/AI and Data Science teams to establish security and compliance guardrails for model development, training data governance, model monitoring, and responsible AI deployment
• Conduct and oversee risk assessments specific to AI/ML systems, including risks related to data poisoning, model integrity, bias, prompt injection, and supply chain threats in the AI ecosystem
• Stay ahead of the rapidly evolving AI regulatory landscape and proactively position Klaviyo's governance posture to meet or exceed emerging requirements

Drive Cross-Functional Impact

• Partner with Product and Engineering leadership to ensure security and compliance are built into product design from day one—acting as a trusted technical advisor, not a blocker
• Collaborate with Legal and Privacy teams to operationalize regulatory requirements and ensure alignment between legal interpretation and technical implementation
• Work with Sales, Customer Success, and Trust teams to support customer-facing security and compliance needs, including customer audits, security questionnaires, and trust documentation
• Engage with executive leadership and the Board to communicate risk posture, compliance status, and strategic GRC investments in clear, business-relevant terms

Get Your Hands Dirty

• Roll up your sleeves and do the work—conduct technical risk assessments, review architecture designs, write automation scripts, troubleshoot control gaps, and dive into the details when it matters
• Personally lead critical compliance initiatives, audit responses, and incident-driven governance activities when the stakes are high
• Maintain deep technical currency by staying hands-on with cloud platforms (AWS, GCP, Azure), infrastructure-as-code tools, security tooling, and modern software development practices

What We're Looking For

Must-Haves

• 10+ years of experience in security, governance, risk, and compliance, with at least 5 years in a leadership role building and scaling programs at high-growth technology or SaaS companies
• Strong engineering and technical foundation—you've written code (Python, Go, or similar), built automation, worked in cloud-native environments, and can engage deeply with engineering teams on technical design and implementation
• Deep expertise across multiple compliance frameworks including ISO 27001, ISO 42001, ISO 27017, ISO 27018, SOC 2, HIPAA, GDPR, and SOX IT controls, with a demonstrated ability to rationalize and unify controls across overlapping frameworks
• Demonstrated experience in AI/ML security and governance, including familiarity with AI-specific risk frameworks, responsible AI principles, and the unique security challenges of machine learning systems
• Hands-on experience with cloud infrastructure and security (AWS strongly preferred), including understanding of IAM, networking, encryption, logging/monitoring, and infrastructure-as-code (Terraform, CloudFormation, etc.)
• Proven ability to build compliance-as-code and automated GRC capabilities, including evidence collection automation, continuous monitoring, and integration with engineering toolchains
• Exceptional cross-functional leadership skills—you've successfully partnered with Engineering, Product, Legal, and executive stakeholders to drive security and compliance outcomes without relying on authority alone
• Experience managing external audits and regulatory examinations end-to-end, with a track record of clean results and efficient audit processes

Strong communication skills with the ability to translate complex technical and regulatory concepts for diverse audiences—from engineers to board members

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

ABOUT THE TEAM:

The Developer Platform team builds the tools and infrastructure that power software development at Anduril. We own the company's primary developer CLI (2,300+ engineers, 93k+ invocations), CI/CD pipelines serving 3,500+ engineers across 23 product lines in the US, Australia, and UK, deployment and release management systems, and Anduril's LLM adoption platform. We are standing up a new agentic development initiative to build the next generation of AI-powered developer infrastructure. The team is growing fast and this is a ground-floor opportunity to define what agentic software development looks like at a company building mission-critical defense systems.

WHAT YOU'LL DO:

• Build multi-agent orchestration infrastructure that moves AI coding agents from individual developer machines to servers executing work autonomously across repositories at company scale
• Design and implement an agent-optimized, real-time knowledge base that gives AI agents deep context on codebases, architecture, and operational patterns
• Build a skills and plugin platform that lets any team encode their domain knowledge into reusable AI capabilities
• Improve CI/CD reliability and developer experience across 23 product lines
• Create release tooling that simplifies shipping software to production environments and robotic platforms
• Operate and evolve Anduril's LLM adoption platform: model rollouts, capacity management, cost attribution, and developer onboarding

REQUIRED QUALIFICATIONS:

• Strong software engineering fundamentals in one or more of: Go, Python, TypeScript
• An entrepreneur, builder, PM, and designer rolled into one. We need people with outstanding software taste who can identify the right problem, design the solution, build it, and ship it in days, not quarters.
• A passion for developer tooling. You notice friction in your own workflow and cannot help but fix it. You spend 4 hours sharpening the axe and 30 minutes chopping wood.
• Demonstrated ability to quickly learn and adapt to unfamiliar technologies across multiple domains
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

PREFERRED QUALIFICATIONS:

• Experience building developer tools, CLIs, CI/CD systems, or platform infrastructure
• Experience with Kubernetes, Nix, or cloud infrastructure (AWS/Azure)
• Genuine interest in LLMs and agentic systems as applied to developer productivity. If you are already building with AI coding agents in your daily workflow, you will feel right at home.
• Prior work on LLM integrations, prompt engineering, or agent frameworks

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

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 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

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.

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

The Opportunity

If you've worked alongside hardware teams, you know the damage that results from a missed change request or critical context that was never relayed to the right person. Reflow exists to close that gap. We're building the first AI-powered platform built for hardware product development, one that listens across the tools teams already use, maintains a structured picture of every program, and proactively coordinates across disciplines when things inevitably change.

This is an early role for a hands-on AI engineer to design and build the agents at the core of our platform, backed by a parent company with deep roots in engineering and manufacturing. You'll own the AI systems that set our product apart: agents that understand hardware workflows, anticipate problems, and take action on behalf of engineering teams.

Who We're Looking For

We're looking for an AI engineer who works equally well in applied research and production software. You've shipped LLM-powered agent systems to real users, you have strong intuitions about prompt engineering, tool use, and orchestration patterns, and you keep up with a field that changes fast. You're comfortable evaluating new frameworks, models, and techniques on short cycles and making pragmatic build-vs.-adopt decisions as the landscape shifts.

We currently use LangChain's DeepAgent framework for our agent orchestration, but every layer of our AI stack is open to change. The right person for this role understands how agent systems work under the hood, not just one framework's abstractions, and can adapt as better tools and approaches emerge.

This senior engineer will work alongside our engineering team and head of product to build, optimize, and operate the AI agents that give users proactive coordination, risk surfacing, status summaries, and AI-generated deliverables. The role is hands-on. You'll write code daily while contributing to AI architecture decisions and helping define how we evaluate and evolve our agent capabilities over time.

What You'll Do

Your day-to-day responsibilities will include:

• Designing, building, and iterating on LLM-powered agents that coordinate across engineering disciplines, surface project risks, and generate structured deliverables (proposals, SOWs, status reports)
• Owning the agent orchestration layer (currently LangChain DeepAgent) and continuously evaluating whether to extend, replace, or supplement it as new frameworks and patterns emerge
• Implementing robust tool-use patterns that connect agents to external systems (project management tools, CAD/PLM platforms, communication channels) via APIs and integrations
• Designing and tuning prompts, chains, and retrieval strategies to maximize agent reliability, accuracy, and usefulness across diverse hardware project contexts
• Building evaluation and observability infrastructure for agent performance, including tracing, cost tracking, latency monitoring, and automated quality benchmarks
• Developing streaming agent interfaces that surface real-time progress, reasoning transparency, and proactive alerts to end users
• Staying current with rapid advances in LLMs, agent frameworks, and related tooling, and translating that awareness into actionable recommendations for the team
• Collaborating with frontend engineers on the UX of AI-powered features and with backend engineers on data pipelines and API design
• Contributing to AI architecture decisions, code reviews, and engineering best practices

Technical Requirements

Must Have:

• 5+ years of production software engineering experience, with 2+ years focused on bringing LLM-based applications or agent systems to market
• Demonstrated proficiency using AI coding tools (Cursor, Copilot, Claude, etc.) to accelerate development
• Hands-on experience building and deploying agentic systems using frameworks such as LangChain/LangGraph, CrewAI, AutoGen, or custom orchestration
• Strong understanding of LLM fundamentals: prompt engineering, function/tool calling, retrieval-augmented generation (RAG), context window management, and token economics
• Proficiency with Python in production environments
• Experience integrating LLM-powered features with external APIs, databases, and third-party tools
• Experience designing and operating background job / async task pipelines (Celery, RQ, Temporal, or similar) for long-running agent runs and reliable retries
• Experience building multi-agent systems with planning, delegation, and inter-agent communication patterns
• Demonstrated ability to evaluate and adopt new AI tools and frameworks quickly, with a track record of staying ahead of a fast-moving field
• Strong software engineering fundamentals: clean architecture, testing, version control, and code review practices
• Ability to balance rapid experimentation with production-grade reliability

Highly Valuable:

• Direct experience with LangChain's DeepAgent or LangGraph for multi-step agent orchestration
• Background in evaluation frameworks for LLM outputs (automated scoring, human-in-the-loop evaluation, regression testing for prompts)
• Familiarity with vector databases and embedding pipelines (Pinecone, Weaviate, pgvector, or similar)
• Experience with model serving infrastructure, fine-tuning workflows, or model selection/routing strategies
• Understanding of authentication/authorization patterns (OIDC, JWT) and secure handling of user data in LLM contexts
• Background in B2B SaaS platforms, project management tools, or technical collaboration products
• Familiarity with hardware development, engineering workflows, or project management concepts (phases, gates, dependencies, requirements traceability)
• TypeScript / React fluency, enough to pair with frontend engineers on streaming agent UIs and reasoning-transparency surfaces

What We Offer

Real Impact: The opportunity to build purpose-built tooling for an entire industry that has never had it

Customer Access: Direct exposure to hundreds of real hardware projects annually through Re:Build's engineering and manufacturing companies

Technical Growth: Hands-on work at the frontier of applied AI, solving novel agent design challenges with real-world feedback loops

Autonomy: Backed by Re:Build while operating with startup independence

Benefits: Full health/dental/vision, bonus program, generous 401K, paid time off, annual learning stipend

Equity & Growth: Participation in Re:Build's LTIP equity program and opportunity for founder equity in potential spin-out

Compensation & Location

Location: Remote-first, with preference for candidates in Boston, Seattle, Los Angeles, or other cities with Re:Build offices

Compensation: Base salary range of $143,000 to $215,000 with performance bonus and long-term incentive plan offered. Potential equity stake under independent spinout scenario.

Please note this role is restricted to US citizens or lawful permanent residents only due to exposure to export controlled information.

About Re:Build Manufacturing

Re:Build Manufacturing is a growing family of industrial and engineering businesses combining enabling technologies, operational superiority, and strategic M&A to build America's next generation industrial company. At Re:Build we deploy deep expertise in engineering, operations management, and technology to supercharge the performance of our member companies. We harness deep professional expertise and a candid, principled operating culture to drive differentiated outcomes. Ours is a fast-paced environment where individuals can stretch and be challenged to pursue their fullest potential.

Re:Build was founded to pioneer a profitable model for the revitalization of US manufacturing. We've assembled a powerful set of complementary capabilities and lines of business that enable us to pursue a wide range of end markets. Our acquired businesses are grounded in build-to-print and by-the-hour engineering and design services, and we're using their combined expertise to migrate to increasingly sophisticated program development and production, as well as the generation of our own products. Our unique set of capabilities lend themselves to highly complex systems and products, and we offer customers a range of services including product and systems design, automation, fabrication, assembly, and large volume contract manufacturing. Our customers span a wide array of industries including aerospace, defense, mobility, healthcare, pharma, biotech, clean tech, chemicals, energy, lifestyle, food production, and industrial equipment.

We want to work with people that reflect the communities in which we operate

Re:Build Manufacturing is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, marital status, parental status, cultural background, organizational level, work styles, tenure and life experiences. Or for any other reason.

Re:Build is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at accommodations.ta@ReBuildmanufacturing.com or you may call us at 617.909.6275.

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. 

Data & Analytics

Accordion's Data & Analytics (D&A) team offers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges.

We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics.

This role can be based in any of our US office locations and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location.

This position is not eligible for immigration sponsorship.

Accordion Intelligence Lab

The AI Lab is composed of leading software and AI engineers, designing agentic-AI solutions ahead of the market. Our group builds and operationalizes the AI systems that power Accordion’s consulting capabilities, from agentic architectures and RAG pipelines to evaluation frameworks and production observability.

The Lab works closely with practice leaders to translate research findings into scalable, reliable tools that advance Accordion’s AI-driven value creation work for PE clients and their portfolio companies.

About the Role

We’re looking for experienced AI Engineers to join new AI-augmented delivery pods: purpose-built teams that combine AI engineering, data science, and product management to transform how PE-backed companies run finance and operations.

In this role, you will design and build the AI systems that power client engagements: agentic workflows, RAG pipelines, evaluation frameworks, and production-grade tools that operate in real PE environments. You’ll work directly with clients and cross-functional pod teammates from day one, and you will be expected to ship fast, defend your decisions, and continuously raise the bar on what AI-assisted delivery looks like.

This is a highly technical, hands-on role. We move at sprint pace—not quarter pace. If you want to move quickly, own outcomes end-to-end, and build things that matter in finance, this is the role.

What You’ll Do

• Design and build multi-agent systems and RAG pipelines that automate financial workflows for PE-backed portfolio companies
• Own the full stack from prompt engineering and tool design through deployment and monitoring
• Practice eval-driven development: define how success is measured before you build
• Translate ambiguous client problems into engineering requirements and deliver results in compressed timeframes
• Present and defend architectural decisions to technical and non-technical audiences—including CFOs and PE operators
• Build observability and evaluation infrastructure to continuously improve production AI system quality
• Travel to client site as needed

Success in the First 6 Months

• Work with like-mined AI engineers to ship at least one end-to-end agentic solution in a client engagement, from scoping through production
• Establish evaluation infrastructure for your pod’s systems so that quality is measurable and regressions are caught early
• Demonstrate materially faster delivery cycles because of how you use AI tools—not just that you use them
• Build a reputation within the pod and with clients as someone who can be handed a hard problem and trusted to return a working, defensible solution

What You’ll Bring

• AI tools are woven into how you work daily—you are materially faster because of it, and you can demonstrate that concretely
• 3–8+ years of software engineering experience with a notable portion in AI/ML systems, agent development, or applied LLM engineering
• Hands-on experience building production LLM applications: RAG systems, agentic workflows, tool use, multi-agent orchestration
• Proficiency in Python; experience with LangChain, LangGraph, AutoGen, DSPy, or equivalent orchestration frameworks
• Strong grasp of evaluation methodologies: designing evals, catching regressions, assessing LLM output quality
• Solid data engineering fundamentals: ETL design, SQL/NoSQL, vector databases, streaming or batch pipelines

Nice to Have

• Open-source contributions in the AI/ML space
• Finance or PE domain experience: FP&A, GL data, ERP systems (NetSuite, SAP), or financial workflow automation
• Experience building tools for reuse across multiple clients or in multi-tenant architectures
• Prior experience in consulting, professional services, or client-facing delivery environments

This is a high-velocity environment. Sprints are short, client expectations are high, and we don’t slow down between engagements. If you’ve spent time in large enterprise engineering organizations where velocity is constrained by process, this will feel different.

The people who thrive here are those who find the pace energizing, not exhausting. They ship fast because they’ve internalized good judgment—not because they cut corners. They use AI tools to multiply their output, communicate clearly with non-technical stakeholders, and course-correct quickly when something isn’t working.

The annual salary for this role ranges from: $144,500 to $230,000 USD + significant bonus + benefits. 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-BS1

At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo to power our products and develop AI agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business.

As a Sr. AI Engineer at Klaviyo, you’ll play a key role in designing and building scalable backend systems and user experiences that power our AI products and AI agent solutions. You’ll partner closely with product managers, machine learning engineers, and data scientists, to drive real-world impact at scale. This is a backend-heavy role with opportunities to influence architecture, async processing pipelines, distributed systems, and more.

How You Will Make a Difference

• Design and build backend systems that support scaling our AI solutions for 167K+ customers.

• Develop robust, reliable and scalable data collection and processing pipelines for machine learning models to train and consume.

• Develop robust, reliable and scalable services to serve AI models in production environments.

• Contribute to evolving our agentic architecture — making our AI agents more self-sufficient and performant.

• Contribute to a culture of ownership, experimentation, and customer-centric product thinking.

Who You Are

• 5–7 years of professional experience in software engineering, with a strong focus on backend systems and distributed architectures.

• Have hands-on experience building and deploying generative AI and agentic AI applications into production, with expertise in prompt engineering, few-shot learning, fine tuning and evaluation.

• Experienced backend engineer with a strong track record of building scalable, distributed systems, especially in the service of AI agent capabilities.

• Proficient in Python and modern backend frameworks (FastAPI, Django preferred).

• Experience creating human and automated evals to ensure high AI model quality.

• Proficient in big data tools such as Apache Spark and Hadoop.

• Deep experience with asynchronous processing and distributed task queues (Celery, Kafka, SQS, RabbitMQ, Redis).

• Strong understanding of database technologies and ORMs (SQLAlchemy, Alembic).

• Comfortable with cloud-native architectures (AWS) and container orchestration (Kubernetes); can manage infrastructure and CI/CD pipelines.

• Skilled at designing and building robust APIs.

• Able to operate with a high degree of autonomy, handle ambiguity, and thrive in a fast-moving, startup-like environment.

• Driven by curiosity. You're someone who learns and stays up to date with this rapidly evolving field.

• Comfortable collaborating directly with product managers and customers to shape solutions.

Nice to Have

• Trained ML models in the past and deployed them in production systems to generate impact to businesses.

• Experience in reinforcement learning.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, 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 April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

About the role:

As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models.

Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.

Responsibilities:

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers like MCP servers, sub-agents, and agent skills that will be used in production workflows.
• Provide white glove deployment support for Anthropic products in enterprise environments.
• Identify and codify repeatable deployment patterns and contribute insights back to our Product and Engineering teams.
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks.
• Build long term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Potential Travel (based on location) to customer sites to build in person with customers. - Estimated 25% 
• Be a champion for Anthropic’s mission in the field.

You May Be a Good Fit If You Have:

• 3+ years of experience in a technical, customer facing role such as Forward Deployed Engineer, or as a Software Engineer with consulting experience. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale.
• Strong programming skills with proficiency in Python (and ideally in one or more additional languages like Typescript, Java, etc) and experience shipping production applications 
• High agency with an ability to navigate ambiguity present in complex organizations.
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity.
• Passion for advancing safe, beneficial AI systems through creative technical applications.
• Strong communication skills to conduct discovery with customers and to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach.
• A background in financial services, healthcare/life sciences, or another enterprise vertical is a plus.
• Experience with enterprise IT systems and/or AI deployment patterns is a plus.
• Experience working as an FDE or in a professional services context is a plus.

About the role:

As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to Digital Native Businesses - technology companies adopting the Claude API into their core products. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting-edge implementation patterns for LLMs.

Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.

Responsibilities:

• Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
• Partner with account executives and solutions architects to translate customer business requirements into technical solutions
• Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites
• Lead hands-on technical workshops and code reviews with customer engineering teams
• Identify common design patterns and contribute insights back to our Product and Engineering teams
• Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques
• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
• Travel occasionally to customer sites for workshops, implementation support, and building relationships
• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have:

• 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.
• Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale
• Strong programming skills with proficiency in Python or TypeScript and experience building production applications
• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
• Passion for advancing safe, beneficial AI systems through creative technical applications
• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Please note this role requires 3 days in office per week. 

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

We are seeking a talented and innovative Synthetic Data Engineer. In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of data processing and model training within the organization.

Responsibilities:

• Design domain-specific synthetic data generation (SDG) pipelines via self-instruct and constitutional prompting.
• Implement automated quality scoring and de-duplication systems.
• Manage data pipelines that feed directly into SFT and DPO training loops.

Qualifications:

• Proven experience building large-scale data pipelines (Airflow, Spark, Ray).
• Deep knowledge of prompt engineering for data generation.
• Familiarity with dataset distillation and bias mitigation.

At Klaviyo, the ARIA (Applications, Resources, Intelligence, and Automations) team is building the AI systems that transform how our employees work. We are looking for a Senior AI Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools from the ground up. This role sits at the intersection of applied AI research and full-stack software engineering. You will own everything from LLM integration architecture and RAG system design to CI/CD pipeline management and production observability. If you want to build AI that real people use at scale every day, this is the role for you.

You will report into the Director of AI and App Engineering and ….

How you’ll make a difference:

• Design and build LLM-powered applications: Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance.
• Build and maintain AI integration pipelines: Design robust, scalable API integrations between AI models and internal systems such as HRIS, ticketing, CRM, and knowledge bases, ensuring reliability, low latency, and high availability.
• Develop full-stack AI features end-to-end: Own the complete development of AI features across the stack from backend model orchestration and API layers to frontend interfaces that make AI accessible to non-technical employees.
• Architect and manage CI/CD pipelines for AI systems: Build and maintain automated deployment pipelines for AI models and services, including model evaluation frameworks, A/B testing infrastructure, and safe rollout strategies.
• Implement RAG and retrieval systems: Design and build retrieval-augmented generation systems grounded in Klaviyo internal knowledge, ensuring accuracy, relevance, and up-to-date responses at scale.
• Evaluate and fine-tune AI models: Lead benchmarking, evaluation, and fine-tuning of foundation models for Klaviyo use cases, including prompt engineering and parameter-efficient fine-tuning techniques.
• Establish AI engineering best practices: Define coding standards, testing frameworks, and architectural patterns for AI development at Klaviyo, enabling the team to ship reliable AI features consistently.
• Build AI observability and monitoring tooling: Instrument AI systems with latency monitoring, output quality evaluation, hallucination detection, cost dashboards, and production alerting.
• Collaborate with Product and Data Science: Work closely with PMs, data scientists, and ML engineers to translate requirements into technical implementations, maintaining a tight feedback loop between experimentation and production.
• Drive security and compliance in AI systems: Ensure AI integrations follow data privacy best practices, implement guardrails for sensitive data handling, and maintain compliance with Klaviyo security and governance standards.

Who you are: 

• 3+ years of software engineering experience, with at least 2 years focused on building AI, ML, or LLM-powered systems in production.
• Deep expertise with large language models such as OpenAI, Anthropic, Mistral, or Llama, and experience integrating them into production applications via API.
• Strong full-stack engineering skills across Python (FastAPI, Flask, or Django) and TypeScript or JavaScript, with experience in modern frontend frameworks.
• Proven experience designing and building CI/CD pipelines for software or ML systems using tools such as GitHub Actions, Jenkins, or CircleCI.
• Experience with RAG systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models.
• Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code tools such as Terraform or Pulumi.
• Experience with prompt engineering, model evaluation frameworks, and LLM observability tools such as LangSmith or Weights and Biases.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, 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 April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

At Klaviyo, the ARIA (Applications, Resources, Intelligence, and Automations) team is building the AI systems that transform how our employees work. We are looking for a Senior AI Engineer to design, build, and scale production-grade LLM integrations and AI-powered automation tools from the ground up. This role sits at the intersection of applied AI research and full-stack software engineering. You will own everything from LLM integration architecture and RAG system design to CI/CD pipeline management and production observability. If you want to build AI that real people use at scale every day, this is the role for you.

You will report into the Director of AI and App Engineering and ….

How you’ll make a difference:

• Design and build LLM-powered applications: Architect and develop production-grade systems leveraging large language models (GPT-4, Claude, Mistral, Llama) for internal automation, knowledge retrieval, and intelligent workflow assistance.
• Build and maintain AI integration pipelines: Design robust, scalable API integrations between AI models and internal systems such as HRIS, ticketing, CRM, and knowledge bases, ensuring reliability, low latency, and high availability.
• Develop full-stack AI features end-to-end: Own the complete development of AI features across the stack from backend model orchestration and API layers to frontend interfaces that make AI accessible to non-technical employees.
• Architect and manage CI/CD pipelines for AI systems: Build and maintain automated deployment pipelines for AI models and services, including model evaluation frameworks, A/B testing infrastructure, and safe rollout strategies.
• Implement RAG and retrieval systems: Design and build retrieval-augmented generation systems grounded in Klaviyo internal knowledge, ensuring accuracy, relevance, and up-to-date responses at scale.
• Evaluate and fine-tune AI models: Lead benchmarking, evaluation, and fine-tuning of foundation models for Klaviyo use cases, including prompt engineering and parameter-efficient fine-tuning techniques.
• Establish AI engineering best practices: Define coding standards, testing frameworks, and architectural patterns for AI development at Klaviyo, enabling the team to ship reliable AI features consistently.
• Build AI observability and monitoring tooling: Instrument AI systems with latency monitoring, output quality evaluation, hallucination detection, cost dashboards, and production alerting.
• Collaborate with Product and Data Science: Work closely with PMs, data scientists, and ML engineers to translate requirements into technical implementations, maintaining a tight feedback loop between experimentation and production.
• Drive security and compliance in AI systems: Ensure AI integrations follow data privacy best practices, implement guardrails for sensitive data handling, and maintain compliance with Klaviyo security and governance standards.

Who you are: 

• 3+ years of software engineering experience, with at least 2 years focused on building AI, ML, or LLM-powered systems in production.
• Deep expertise with large language models such as OpenAI, Anthropic, Mistral, or Llama, and experience integrating them into production applications via API.
• Strong full-stack engineering skills across Python (FastAPI, Flask, or Django) and TypeScript or JavaScript, with experience in modern frontend frameworks.
• Proven experience designing and building CI/CD pipelines for software or ML systems using tools such as GitHub Actions, Jenkins, or CircleCI.
• Experience with RAG systems, vector databases (Pinecone, Weaviate, pgvector), and embedding models.
• Proficiency with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and infrastructure-as-code tools such as Terraform or Pulumi.
• Experience with prompt engineering, model evaluation frameworks, and LLM observability tools such as LangSmith or Weights and Biases.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, 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 April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

Job Title: Sr. Lead AI Engineer
Location: Boston, MA

This role is based in our Boston, MA hub (Hybrid-3x week). 

About the Role

At Klaviyo, we believe the future of software isn’t just better productivity tools for humans—it’s systems that can run, optimize, and adapt themselves based on outcome and reward signals. We’ve already built the infrastructure and applications that sit between businesses and consumers—serving 183,000+ customers, billions of consumer profiles, and hundreds of billions of messages and conversion events. Now we’re investing heavily in Marketing AI and Service AI: the shared services and agentic capabilities that power AI‑native experiences across Klaviyo.

As a Sr. Lead AI Engineer in the AI & Analytics organization, you’ll be the technical leader for a set of high‑impact AI services and agentic systems. You’ll own architecture and execution for complex, distributed backend systems; guide other engineers through design and implementation; and partner closely with product, machine learning, and data science to turn AI ideas into reliable, scalable production capabilities. This is a hands-on tech lead role, not a people‑manager role.

How You’ll Make a Difference

• Define and improve the engineering architecture for Service and Marketing AI capabilities. Lead the design of scalable, low‑latency backend systems and APIs that power our AI products and agents for 183K+ customers, handling billions of events and interactions.
• Build and harden AI serving systems. Lead the development of services that host and orchestrate AI models (LLMs, tools, evaluators, retrieval systems), with clear contracts, SLOs, and observability so other teams can depend on them.
• Evolve our agentic architecture. Drive the technical roadmap for Service and Marketing AI agents—improving tool use, autonomy, and reliability so agents can safely take actions on behalf of customers and internal users with minimal human intervention.
• Set engineering standards for AI services. Establish best practices for evaluation, safety/guardrails, prompt and model versioning, offline and online tests, and incident response for AI‑backed systems; hold the bar for design reviews and code quality.
• Lead cross‑team technical work. Act as the primary technical interface between Service / Marketing AI and other product/platform teams—clarifying ownership boundaries, aligning on interfaces, and unblocking dependencies across hubs and time zones.
• Mentor and uplevel engineers. Coach senior and mid‑level engineers through design, implementation, and operational best practices, helping them grow into stronger system owners and future tech leads.
• Help build the Palo Alto hub. Shape local engineering rituals, help with hiring and onboarding, and create healthy patterns for cross‑hub collaboration so work and career opportunities are not constrained by geography.
• Measure what matters. Define and track key metrics for your systems—availability, latency, cost‑to‑serve, agent success rates, eval scores, and customer adoption—and use those insights to drive roadmap and technical decisions.
• Transform engineering and product development workflows by putting AI at the center, building & utilizing agentic coding tools and AI-first working.

Who You Are

• Seasoned backend engineer & tech lead. 8+ years of professional software engineering experience with a strong focus on backend and distributed systems; you’ve led complex projects or areas end‑to‑end and acted as the go‑to technical owner for key services.
• Hands‑on with generative & agentic AI in production. You’ve built and shipped generative or agentic AI applications (e.g., LLM‑backed flows, tool‑using agents, retrieval‑augmented systems) and are comfortable with prompt design, few‑shot approaches, fine‑tuning, and evaluation.
• Deep experience with large‑scale distributed systems. You’ve architected and operated reliable services, async processing pipelines, and distributed task queues (e.g., Celery, Kafka, SQS, RabbitMQ, Redis) supporting high‑throughput workloads.
• Strong Python and data tooling fluency. Proficient in Python and modern backend frameworks (FastAPI, Django or similar), with experience using big data tools such as Spark/Hadoop and ORMs like SQLAlchemy/Alembic.
• Production‑grade cloud experience. Comfortable with AWS and Kubernetes, CI/CD pipelines, observability, and operational best practices; you treat infrastructure choices as part of the system design, not an afterthought.
• Evaluation and quality‑obsessed. You’ve designed human and automated evals for AI systems, know how to instrument for quality, and understand how to balance latency, cost, and response quality in real‑world usage.
• Technical leader, not just individual contributor. You influence architecture beyond your own code, facilitate design reviews, rally cross‑functional partners, and help teams converge on pragmatic decisions in ambiguous spaces.
• Collaborative and customer‑first. You’re comfortable collaborating directly with PMs, ML engineers, and customers; you can translate between customer needs, product goals, and technical constraints, and you care deeply about the customer experience.
• You’ve already been effectively practicing agentic coding in your daily work. You’re hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.
• Bonus: You use AI tools to accelerate exploration, shorten iteration cycles, and bring sharper ideas to the table—for yourself and your teammates.

Nice to Haves

• Prior experience training and deploying ML models (including RL or RLHF) into production systems that drove measurable business impact.
• Experience building shared AI/ML platforms or services used by multiple product teams.
• Background in marketing tech, ecommerce, or other domains where customer data, personalization, and experimentation are central.

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, 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 April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

About the Team

• This role is part of our Data Science team which is the largest team in our organization consisting of over 200+ Data Scientists throughout the world.
• Our Data Scientists work in a full lifecycle role and on a broad range of subjects acquiring extensive technical and professional experience in data science, data engineering, coding, business understanding and client engagement.
• Our company is small enough that each person’s achievements has an impact on our overall performance, yet big enough to be a world leader and innovator in our domain.
• As a member of the data science team, you will be working alongside our technical experts and your role will be key to rolling out our enterprise level solutions to our clients.

Key Responsibilities

• Your role will be to actively contribute to the US- Insurance roadmap and clients, and working on various data types such as structured data, free text, documents and images. 
• Build and productionize data pipelines (structured, text, documents, images) optimized for LLMs and multi-modal models.
• Design, develop and deploy LLM-based solutions (RAG, embeddings, instruction tuning) for subrogation, claims handling, document understanding, and related use cases.
• Experiment with the latest in Agentic AI technologies (Langchain/Langgraph, OpenAI Agent SDK, MCP, A2A) and develop MVP for the next generation of autonomous subrogation solutions.
• Develop "Chain-of-Thought" and "ReAct" prompting strategies to ensure the agent can justify its liability percentages based on the Comparative Negligence laws of different jurisdictions.
• Create custom "tools" for the agent, allowing it to query internal databases, call external weather APIs, or calculate impact force based on telemetry data.
• Establish rigorous evaluation frameworks (LLM-as-a-judge) to ensure the agent’s decisions are unbiased, legally sound, and explainable.
• Ensure responsible-AI practices: privacy, hallucination mitigation, explainability and compliance.
• Lead client workshops, present prototypes, gather feedback and help define roadmap priorities.

WHAT WE ARE LOOKING FOR

We are looking for candidates with diverse skills to help us build excellent technology solutions for our clients and be proficient in the following skills:

• Expert proficiency in production-level object-oriented programming (OOP) for building scalable and reliable systems.
• Proven hands-on experience with Large Language Models (LLMs) and generative AI techniques (including RAG, embeddings, prompt engineering, and model tuning), leveraging frameworks such as OpenAI/Anthropic or open-source variants.
• Solid foundation in ML fundamentals with practical experience in the full machine learning lifecycle, including model evaluation, monitoring, versioning, and deployment in production environments.
• Experience designing and implementing robust data pipelines for document, OCR, and multi-modal data workflows.
• Agentic Frameworks: Experience with integrating frameworks like LangChain/LangGraph, OpenAI Agent SDK, CrewAI, A2A/MCP with Databricks or Azure-hosted models (e.g., DBRX, OpenAI GPT-5.3, Anthropic Claude, Google Gemini).
• Demonstrated ability to effectively engage with clients, translate complex business needs into clear, actionable technical solutions, and manage stakeholder expectations.

Highly Desired Skills

• Databricks Ecosystem: Deep expertise in Mosaic AI (formerly MosaicML), Unity Catalog, and Delta Lake.  Good understanding of Spark data architecture is a plus.
• Experience using MLflow for the full lifecycle: from experiment tracking and prompt engineering in the AI Playground to model evaluation.

 #LI-MG1