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

Okta’s Business Technology organization builds secure and intelligent internal platforms that power our global workforce. Our AI & Automation team is delivering next-generation tools and experiences by integrating GenAI and intelligent automation into workflows across IT, HR, Finance, Sales, Marketing and Customer Support.

We focus on real-world applications: virtual agents, AI copilots, internal RAG services, and AI-augmented self-service portals — all with scale, governance, and user experience in mind.

The Opportunity

As a Senior Software Engineer, Applied AI, you’ll play a key role in building user-facing and backend systems that leverage GenAI to improve internal experiences and operations. This role requires strong full-stack engineering skills, with an emphasis on both AI integration and building intuitive, performant UIs that make AI accessible and useful to our internal customers.

You’ll work closely with software engineers, product managers, and designers to build secure, intelligent tools for employees across Okta.

What You’ll Do

• Design and build end-to-end GenAI-powered applications, including web-based UIs, API services, and backend orchestration.

• Implement and integrate LLM-based experiences using frameworks like LangChain, LlamaIndex, and tools like OpenAI, Claude, or Gemini.

• Define, implement, and champion operational excellence standards (SLOs, observability, incident response frameworks) for all services deployed.

• Develop responsive, accessible, and modern frontend interfaces using frameworks like React or Vue — with a focus on usability, performance, and trust in AI outputs.

• Build and maintain a library of reusable frontend components and hooks that allow other business delivery teams to easily "drop in" GenAI capabilities into their own applications.

• Build and maintain retrieval-augmented generation (RAG) pipelines with vector search and embedding strategies (e.g., Pinecone, FAISS, Qdrant).

• Collaborate with designers and product managers to rapidly iterate on UX patterns for AI-powered experiences (e.g., prompt inputs, citations, summaries).

• Ensure security, privacy, observability, and test coverage across the full stack.

• Contribute to architecture decisions, engineering standards, and best practices for AI/automation systems.

• Partner with platform and infrastructure teams to ensure services scale reliably across the org.

What You’ll Bring

• 5–8 years of software engineering experience with full-stack development, including 2+ years of building AI/ML-driven applications.

• Strong Python development skills and 5+ years experience building cloud-based services using AWS, Docker, and RESTful APIs.

• 2+ years of experience in frontend technologies like React, TypeScript, or Vue, and comfort working on UI/UX for internal tools or enterprise applications.

• Hands-on experience with LLM integration, RAG pipelines, prompt engineering, or orchestration frameworks like LangChain or LlamaIndex.

• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).

• Familiarity with secure coding, authentication/authorization, and internal data governance best practices.

• Ability to collaborate across engineering, design, and product teams — with a strong sense of user empathy and technical ownership.

• Bonus: Exposure to design systems, AI evaluation tooling, or real-time application performance monitoring.

Why Join Okta

• Make AI Real: Design and build AI-powered apps used daily by Okta employees.

• Full-Stack Challenge: Tackle end-to-end problems — from LLM orchestration to intuitive UIs.

• Trusted Innovation: Join a team committed to security, ethics, and technical excellence in AI.

#LI-MK1

#LI-hybrid

P24739_3355024

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

ABOUT THE TEAM

Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril’s competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB

We are looking for a talented full stack software engineer to join our growing team at Anduril Labs in Washington, DC. As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts. As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components. You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms). Embedded software development experience is a plus. You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs. Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization. Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company. This means you will get to directly contribute to the development of Anduril’s next-generation products and services. So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

WHAT YOU’LL DO

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.
• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.
• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.
• Support Anduril- and customer-funded R&D efforts.
• Participate in field experiments and technology demonstrations.

REQUIRED QUALIFICATIONS

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.
• Proven software architecture and design skills.
• Ability to quickly understand and navigate complex systems and established codebases.
• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).
• Web app development (e.g., React, Angular, or Vue).
• Cloud development (e.g., AWS, Azure, or GCP).
• Data modeling and wrangling.
• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory)
• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).
• API development and integration (e.g., REST, GraphQL).
• Containerization technologies (e.g., Docker, Kubernetes).
• Software development on Linux and Windows.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• BS in Computer Science, Engineering, or similar field.
• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).
• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).
• Mobile app development (e.g., iOS or Android).
• Embedded software development experience.
• Willingness to travel up to approximately 10%

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

Description

Reusable launch systems are the key to seamlessly connecting Earth and space. An instrumental ingredient to making reusable launch vehicles is the ability to move fast. That is our goal for Boltline by Stoke Space, our commercial software platform that helps advanced hardware manufacturing teams integrate, track, iterate, build, and test efficiently. 

As a Senior AI Engineer on the Boltline team, you will design, build, and deploy intelligent systems that augment our platform's capabilities—from agentic workflows that automate complex manufacturing processes to RAG pipelines that surface critical institutional knowledge. You'll architect evaluation frameworks to ensure AI reliability, build developer tooling that empowers the team, and integrate LLMs into production systems that accelerate hardware development. The ideal candidate demonstrates deep expertise in applied AI/ML, a high degree of ownership, and curiosity—balancing fast execution with robust, production-grade engineering. 

Responsibilities

• Design and implement agentic systems and workflows that automate complex, multi-step manufacturing and engineering processes 
• Build and maintain RAG pipelines leveraging vector databases to enable intelligent search and retrieval 
• Develop comprehensive evaluation frameworks (evals) to measure, monitor, and improve AI system performance, accuracy, and reliability 
• Create developer tooling, SDKs, and internal platforms that accelerate AI adoption across the engineering organization 
• Integrate LLM APIs and orchestration frameworks into production applications 
• Design end-to-end features across the stack using React, TypeScript, GraphQL, and Postgres 
• Lead technical design discussions and contribute to architectural decisions for AI-powered features 
• Partner with product and hardware teams to identify high-impact opportunities for AI augmentation 
• Mentor engineers on AI/ML best practices through code reviews, pairing, and design collaboration 
• Participate in Boltline Operational Excellence including participating in on-call rotation and other operational activities 

Qualifications

• 1-5 years of professional software development experience 
• Hands-on experience building agentic systems, autonomous workflows, or AI-powered automation 
• Experience building RAG architectures, integrating vector databases, and deploying semantic search implementations 
• Experience designing and implementing evaluation frameworks for LLM-based systems 
• Proficiency with full-stack development: TypeScript, React, GraphQL, and relational databases 
• Familiarity with LLM APIs (OpenAI, Anthropic, etc.) and orchestration frameworks 
• Proven ability to own features from concept through deployment and iteration 
• Excellent collaboration and communication skills within cross-functional teams 
• Comfort working in a fast-paced, evolving environment with a focus on delivering impact 

Preferred Qualifications

• Degree in computer science or related field/experience 
• Experience with prompt/context engineering and fine-tuning 
• Background in building developer tools, CLIs, or internal platforms 
• Familiarity with Next.js, Apollo (Client/Server), Hasura, or similar 
• Experience with Docker, Kubernetes/ECS, and AWS infrastructure 
• Familiarity with event-driven architectures using Temporal, Kafka, or similar 
• Hands-on experience with observability and monitoring for AI systems 
• Exposure to manufacturing, aerospace, or complex physical systems 
• Interest in aerospace/manufacturing workflows 

Benefits

• Equity – We know that our employees are the reason we succeed. To give everyone a stake in our future, we are pleased to offer equity in the form of stock options to all regular, full-time employees. 
• Comprehensive benefits program including subsidized medical, dental, and vision insurance 
• Company-paid life and disability insurance 
• 401(k) plan with employer match 
• 4 weeks’ Paid Time Off  
• Holidays – 10 days (including an end-of-year closure) 
• Paid Family/Parental Leave  
• On-site gym or monthly wellness stipend (depending on location) 
• Dog friendly offices! 

Compensation

Target Levels:

• Level 3 Range: $154,350 - $231,525
• Level 4 Range: $192,885 - $289,380
• Level 5 Range: $231,525 - $347,235

Our job posts are intentionally written to attract a wide variety of experience levels, and we make decisions about the right fit on a per-candidate basis. 

Your actual level and base salary will be decided based on your specific experience and skill level.

Who we are

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

Who you are

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

What you'll do

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

What we're looking for

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

While not required, these are a plus:

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

Our Stack

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

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

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

What We're Looking For

We are looking for a Senior Application Security Engineer to help secure our AI, machine learning, and inference platforms. This is a hands on technical role focused on building security into modern AI infrastructure, inference systems, and developer platforms.

You will work closely with platform engineers, ML engineers, and infrastructure teams to identify risks, design secure architectures, and build security tooling that enables engineers to move quickly and safely.

This role is execution focused. You will drive technical implementation, perform deep security reviews, and help build out our application security capabilities alongside the CISO and engineering leadership.

This role can be based out of one of our office hubs (San Francisco or Seattle) with in-office requirements of at least 2 days per week, plus occasional team/company offsites. We are not able to offer visa sponsorship for this position at this time.

What You’ll Do

Secure AI and Machine Learning Systems

• Perform threat modeling across AI platforms, inference services, and ML pipelines
• Identify risks such as prompt injection, model extraction, adversarial inputs, and data leakage
• Review model serving architectures and inference pipelines
• Partner with ML engineers to secure training, fine tuning, and deployment workflows
• Help design isolation and security controls for multi tenant AI workloads

Application Security Engineering

• Perform architecture and design security reviews
• Conduct targeted code reviews for high risk components
• Identify security gaps in APIs, micro-services, and distributed systems
• Build secure patterns for authentication, authorization, and service to service communication
• Help engineering teams implement secure defaults and guardrails

Inference Platform Security

• Secure customer facing inference APIs and services
• Protect against abuse, model extraction, and adversarial behavior
• Design rate limiting, isolation, and workload protection controls
• Build monitoring and detection for anomalous inference behavior

AI Supply Chain and Model Security

• Evaluate open source models and dependencies
• Secure model artifacts and distribution pipelines
• Implement integrity validation and provenance controls
• Help secure container images and runtime environments

Security Automation and Tooling

• Build security automation for AI and application pipelines
• Integrate security scanning into CI/CD workflows
• Develop tooling to help engineers detect and fix issues early
• Improve developer experience with security guardrails

What You'll Need

Required Experience

• Strong background in application security engineering
• Experience performing threat modeling and architecture reviews
• Experience securing APIs and distributed systems
• Experience working in cloud environments such as AWS, GCP, or Azure
• Experience with containers and Kubernetes
• Strong scripting or programming skills such as Python, Go, or similar
• Experience working closely with engineering teams to implement security improvements

AI and Machine Learning Experience

• Experience securing ML pipelines, inference systems, or data platforms
• Familiarity with risks such as prompt injection, model extraction, and adversarial inputs
• Experience reviewing model serving architectures
• Understanding of training data security and data leakage risks

It's a Strong Plus If You Have

• Red team or offensive security experience
• Experience crafting payloads and evaluating CVEs for exploitability in diverse environments
• Experience with GPU infrastructure or high performance computing
• Experience with Hugging Face, PyTorch, TensorFlow, or similar frameworks
• Experience with LLM systems, RAG pipelines, or agent frameworks
• Experience building security automation pipelines
• Experience securing multi tenant infrastructure

What Success Looks Like

• Security is embedded into AI platform architecture early
• Engineering teams ship quickly with secure defaults
• Inference platforms are resilient against abuse and extraction
• Model pipelines are secure and auditable
• Security tooling scales with engineering growth

Why This Role Matters

This role sits at the intersection of application security, AI infrastructure, and developer platforms. You will help define how we secure modern AI systems while enabling engineers to move quickly and safely.

You will work closely with engineering leadership and the CISO to build practical, scalable security capabilities that support rapid innovation in AI and machine learning.

Compensation

Intro to Position

The Lead AI Solutions Engineer, AI Labs, is a foundational role in building NPR's first Generative AI (GAI)-focused product development team. Reporting to the VP of AI Labs, this engineer will be responsible for the technical development and implementation of generative AI solutions. The core mission is to engineer systems that leverage GAI to enhance the quality and actionability of our content metadata, thereby directly supporting the organization's goals of improving content personalization and increasing editorial efficiency. This role involves hands-on work in integrating AI products into core NPR systems, ensuring solutions are scalable, align with ethical guidelines, and are built upon industry best practices. This is a critical opportunity to shape NPR's technical AI adoption and build a new, innovative function.

Responsibilities

• Engineering & Implementation: Design, develop, and deploy scalable Generative AI (GAI) solutions, focusing on enhancing content metadata quality and actionability to meet organizational objectives.
• Architecture & Technical Best Practices: Establish and champion technical best practices for Generative AI systems, including MLOps, RAG architectures, prompt engineering, and model evaluation, ensuring high-quality, maintainable code.
• Cross-functional Development: Collaborate closely with Product Managers, data scientists, software and infrastructure engineers, and relevant subject matter experts to translate product requirements and roadmaps into robust, production-ready AI systems.
• System Optimization & Performance: Implement data-driven methods, A/B testing, and performance monitoring to optimize the efficiency, scalability, and impact of AI models and pipelines.
• Technical Communication: Clearly articulate technical architectures, development progress, and engineering challenges to product and non-technical stakeholders.
• Responsible AI: Integrate ethical AI principles and compliance standards directly into the design and implementation of all AI products, in alignment with company policies.
• Technology Scouting: Research and evaluate emerging AI technologies, frameworks, and industry trends to drive continuous technical innovation within the AI Labs.

The above duties and responsibilities are not an exhaustive list of required responsibilities, duties and skills. Other duties may be assigned, and this job description is subject to change at any time.

Minimum Qualifications

• 8+ years of professional experience in software development, data science, or machine learning engineering, with a focus on building and deploying production systems.
• 2+ years of hands-on experience working with generative AI, machine learning, or data products.
• Expert proficiency in Python and experience creating functional prototypes to validate technical feasibility and user flows.
• Demonstrable understanding and experience building products that leverage Large Language Models, RAG architectures, prompting, function calling, retrieval, vector databases, embeddings, fine-tuning, and model evaluation.
• Familiarity with building and integrating MCP servers and agentic workflows.
• Background in creating QA systems for AI processes and development.
• Excellent communication skills and the ability to clearly articulate technical architectures and challenges to product and non-technical stakeholders.
• A collaborative and respectful approach to work and an ability to adapt quickly to change.
• A deep commitment to the mission of NPR and to the responsible implementation of Generative AI technologies.

Preferred Qualifications

• Experience designing and building highly scalable, production-grade AI/ML pipelines and services.
• Proficiency with cloud platforms, particularly AWS and Google Cloud Platform (GCP) and MLOps tools, particularly MLFlow and Vertex AI. 
• Experience with DevOps practices, including CI/CD and enterprise infrastructure-as-code.
• Experience working in media organizations and an understanding of media delivery systems.

Work Location & Requirements

• Hybrid Permitted: This is a hybrid permitted role. Some aspects of this role require duties better performed at an NPR facility. The employee will be required to be in the office at the Washington, D.C. location at least two days a week. The employee must also reside in an NPR-supported location (D.C., MD, or VA).

Job Type

• This is a full-time, exempt position.

Compensation

Salary Range: The U.S. based anticipated salary range for this opportunity is $187,000 - $208,000 plus benefits. The range displayed reflects the minimum and maximum salaries NPR expects to provide for new hires for the position across all US locations.

NPR Benefits: NPR offers access to comprehensive benefits for employees and dependents. Regular, full-time employees scheduled to work 30 hours or more per week are eligible to enroll in NPR’s benefits options. Benefits include access to health and wellness, paid time off, and financial well-being. Plan options include medical, dental, vision, life/ accidental death and dismemberment, long-term disability, short-term disability, and voluntary retirement savings to all eligible NPR employees. 

Does this sound like you? If so, we want to hear from you.

#LI-HYBRID

Your Mission 

We are seeking a rare combination of disciplines: an experienced Sr. Compliance Engineer with deep AI Subject Matter Expertise (SME) and export compliance background to join our Governance, Risk, and Compliance (GRC) team. This role is responsible for building, implementing, and sustaining the organizational compliance posture across key regulatory and security frameworks — with a primary emphasis on RMF (NIST 800-53 Rev. 5 + Classified Overlays), CMMC Level 3, NIST 800-171 Rev. 3, EAR/ITAR cyber regulations, and — critically - the governance, risk management, and compliance controls surrounding AI/ML systems and large language models (LLMs) deployed across the enterprise. 

As AI becomes embedded in True Anomaly's operations, mission systems, and products, this role serves as the organizational authority on how AI capabilities are adopted, audited, and controlled responsibly. You will architect and operationalize compliance checkpoints and governance gates within LLM pipelines, evaluate AI vendors and platforms (including OpenAI, Anthropic Claude, and others) against classified and unclassified compliance requirements, and ensure AI-driven workflows satisfy both regulatory obligations and internal risk tolerance. 

The ideal candidate brings deep GRC knowledge, hands-on AI/LLM engineering fluency, and the ability to engage credibly with compliance assessors, government partners, and internal AI/ML engineering teams alike. 

Responsibilities 

Compliance Program Execution 

• Lead and support compliance assessment readiness across key organizational frameworks including NIST SP 800-171 Rev. 2 and 3, CMMC Level 3, NIST SP 800-53 Rev. 5, and the NIST Cybersecurity Framework (CSF). 

• Provide direction on cybersecurity readiness to address EAR and ITAR-related controls and requirements. 

• Drive CMMC readiness activities across the organization, including scoping, gap analysis, control implementation validation, evidence collection, and pre-assessment preparation. 

• Review, maintain, and mature System Security Plans (SSPs) to accurately reflect organizational control implementations, system boundaries, and operational practices — including AI/ML system boundaries and data flows. 

• Manage Plans of Actions and Milestones (POA&Ms), tracking open findings to resolution, communicating status to GRC leadership, and coordinating remediation efforts across responsible teams. 

• Conduct internal compliance audits and control effectiveness reviews to ensure ongoing adherence to applicable frameworks and to surface emerging gaps before external assessments. 

• Maintain audit-ready evidence repositories and documentation packages, ensuring traceability between controls, evidence, and framework requirements. 

AI Governance, Risk & Compliance (AI-GRC) 

• Serve as the organizational AI compliance SME — the primary authority on how AI/LLM systems (including OpenAI GPT models, Anthropic Claude, open-source models, and internally developed models) are evaluated, onboarded, and continuously governed within True Anomaly's compliance boundaries. 

• Design, implement, and maintain compliance checkpoints and enforcement gates within LLM pipelines, including:  

• Input/output filtering and content policy enforcement layers 

• Prompt injection detection and mitigation controls 

• Data classification guardrails to prevent CUI, ITAR-controlled, or classified data from flowing into non-authorized AI systems or endpoints 

• Automated audit logging of AI interactions for traceability and incident investigation 

• Model access control and role-based permissions within AI platforms 

• Conduct AI-specific risk assessments, including evaluation of AI vendor data handling practices, model training data provenance, and third-party AI API security postures against NIST AI RMF, NIST SP 800-53 AI overlays, and internal standards. 

• Develop and enforce an AI System Acceptable Use Policy and supporting standards that govern how employees and systems interact with LLMs, including permissible data inputs, output handling, human-in-the-loop requirements, and escalation procedures. 

• Evaluate proposed AI/ML use cases for regulatory risk (EAR/ITAR, CMMC, data privacy) and provide compliance go/no-go determinations with documented rationale. 

• Collaborate with AI/ML engineers and DevSecOps teams to integrate compliance gates into CI/CD pipelines and MLOps workflows, ensuring model changes and prompt changes undergo review before production deployment. 

• Maintain an AI system inventory, tracking all deployed models, APIs, integrations, and associated risk and compliance status. 

• Monitor emerging AI regulatory developments (e.g., EO 14110, NIST AI RMF, DoD AI Ethics Principles, EU AI Act implications for U.S. defense partners) and assess organizational impact. 

Cross-Functional Compliance Enablement 

• Serve as a primary GRC team resource for compliance questions, control guidance, and framework interpretation across engineering, IT, operations, legal, and security teams. 

• Partner with IT and security operations teams to verify that technical controls — including access management, logging, configuration baselines, and incident response procedures — meet CMMC and NIST requirements at an organizational level. 

• Partner with AI/ML engineers, data scientists, and product teams to embed compliance thinking into AI system design, model selection, and deployment architecture. 

• Collaborate with the Enterprise Risk Manager and broader GRC leadership to ensure compliance findings — including AI-specific risks — are reflected in the enterprise risk register and remediation priorities. 

• Support the development of compliance training and awareness materials, including AI-specific training that builds organizational understanding of responsible AI use, LLM risk, and CMMC obligations. 

• Coordinate with external assessors, third-party auditors, and government partners during assessment engagements, serving as a knowledgeable point of contact for evidence walkthroughs and control discussions. 

Qualifications 

• 7+ years of experience in IT security compliance, GRC, or a closely related discipline, with direct ownership of compliance program activities. 

• Demonstrated expertise in NIST SP 800-171, CMMC (Level 2 or 3), and NIST SP 800-53, with hands-on experience conducting gap assessments, implementing controls, and preparing organizations for external audits. 

• Extensive, hands-on experience with AI/LLM systems, including practical knowledge of platforms such as OpenAI (GPT-4/o-series), Anthropic Claude, Meta Llama, Microsoft Azure OpenAI Service, and/or comparable commercial and open-source LLM ecosystems. 

• Demonstrated ability to design, implement, and operationalize compliance controls within LLM pipelines, including guardrail layers, content filtering, audit logging hooks, and data classification enforcement. 

• Working knowledge of AI security risks, including prompt injection, jailbreaking, data exfiltration via LLM outputs, model inversion, and supply chain risks associated with third-party AI APIs. 

• Familiarity with NIST AI Risk Management Framework (AI RMF) and its application to enterprise and defense AI deployments. 

• Strong understanding of SSP development and maintenance, POA&M management, and audit evidence lifecycle practices in an organizational (non-product) compliance context. 

• Proven experience developing and operationalizing information security policies, standards, and procedures across a multi-disciplinary organization. 

• Strong communication skills with the ability to explain compliance requirements — including AI risk concepts — clearly to both technical practitioners and non-technical business stakeholders. 

• Highly organized, with demonstrated ability to manage multiple concurrent compliance workstreams and deadlines in a fast-paced environment. 

• Active or ability to obtain SECRET or TS/SCI security clearance. 

• Must be a U.S. citizen, lawful permanent resident, or protected individual per ITAR requirements (8 U.S.C. 1324b(a)(3)). 

Preferred Qualifications 

• Strong EAR/ITAR background as it pertains to cybersecurity, AI-generated outputs, and policy development. 

• J.D. focusing on technology law, export compliance (EAR and ITAR), AI regulation, or cyber law. 

• Experience building MLOps or AI DevSecOps pipelines with integrated compliance gates, including automated policy enforcement, prompt review workflows, or model change management processes. 

• Hands-on experience with AI safety and alignment tooling (e.g., LangChain guardrails, NeMo Guardrails, Azure Content Safety, OpenAI Moderation API, Anthropic Constitutional AI/policy layer configurations). 

• Experience evaluating AI vendor agreements and data processing agreements against DoD/CMMC/ITAR data handling requirements. 

• Familiarity with DoD AI Ethics Principles, Responsible AI (RAI) frameworks, and emerging federal AI governance requirements (e.g., EO 14110, OMB AI guidance). 

• Industry certifications such as:  

• Certified Information Systems Auditor (CISA) 

• Certified in Risk and Information Systems Control (CRISC) 

• Certified Information Systems Security Professional (CISSP) 

• CMMC Registered Practitioner (RP) or Certified Professional (CP) 

• CompTIA Security+ or equivalent 

• AWS/Azure AI or Security certifications 

• Background in startup, aerospace, defense technology, or SaaS environments operating under DoD compliance obligations. 

• Familiarity with cloud environments — particularly Azure Government, AWS GovCloud, or Azure OpenAI Government deployments — as they relate to organizational control implementation and AI boundary scoping. 

• Experience coordinating with C/3PAOs or supporting CMMC assessments. 

• Working knowledge of DFARS 252.204-7012, ITAR, and supply chain compliance obligations. 

• Familiarity with Agile/Scrum environments and hybrid project delivery models. 

Compensation 

• Base Salary: Denver - $145,000 to $195,000, Long Beach - $150,000 to $205,000, Washington, DC - $150,000 to $205,000 

• Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience. 

Additional Requirements 

• Work Location: Successful candidates will be located near Denver, CO, Long Beach, CA, or Washington D.C. While we observe a hybrid work environment, some work must be done on site. #LI-Onsite

• Work Environment: Standard office setting, working at a desk or in a production factory environment. 

• Physical Demands: May include frequent standing, sitting, walking, bending, and lifting or carrying items up to 20 lbs. 

This position will be open until it is successfully filled. 

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. 

We value diversity of experience, knowledge, backgrounds, and perspectives and harness these qualities to create extraordinary impact. True Anomaly is committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, maternity or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. 

About Nubank

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.

Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Bank. Visit our institutional page https://international.nubank.com.br/careers/

About the role

AI is core to how Nubank builds products — and securing it is one of the most critical and forward-looking challenges in the company. The AI Security team, part of Nubank's Information Technology & Security area, is responsible for ensuring that AI systems are developed and operated safely and securely at scale, across LLM-powered applications, autonomous agents, and the infrastructure that supports them.

As Lead Security Engineer (AI), you will own and drive Nubank's defensive security strategy for AI products and internal tools. You will define frameworks, set technical direction, build runtime protections, and enable engineering teams across the company to ship AI systems securely by default. This role sits at the intersection of cutting-edge AI and high-stakes security — and your work will directly shape how one of the world's largest fintechs builds trustworthy AI at scale.

You'll be Responsible For

• Leading the security strategy for Nubank's AI systems — covering LLM-powered applications, AI agents, and their underlying infrastructure — and building the standards and frameworks that guide secure AI deployment across the company.
• Securing AI agents and autonomous workflows by hardening tool usage, enforcing appropriate permission levels, and monitoring agent behavior and decision-making in production.
• Designing and enabling secure architectural patterns for AI applications, including LLM-based services and agent orchestration systems.
• Developing AI-specific detection and monitoring capabilities to identify abuse, misuse, and anomalous behavior — including telemetry across prompts, responses, tool usage, and agent execution.
• Designing and implementing runtime protections for LLM applications, such as prompt injection detection, jailbreak protection, abuse detection, and output safety controls.
• Collaborating with AI engineers and platform teams to integrate security controls into AI development and deployment pipelines.
• Staying current with emerging threats and AI security trends, translating them into concrete controls, guidelines, and standards across Nubank's engineering organization.

We Are Looking for a Person Who Has

• Deep expertise in product security, application security, or cloud security, combined with hands-on experience building AI agent systems.
• A proven track record leading cross-team technical initiatives — setting standards and driving adoption without direct authority.
• Experience designing and implementing secure systems and controls in production environments.
• Hands-on experience with runtime security controls (input validation, abuse detection, policy enforcement) in high-throughput production systems.
• Solid familiarity with LLM application architectures — including prompt pipelines, tool use, and RAG — and their threat surfaces such as prompt injection, data exfiltration, and jailbreaks.
• Strong understanding of agentic systems and AI infrastructure, with the ability to threat-model novel and non-deterministic systems.
• Experience building monitoring, telemetry, and alerting for production systems.
• Strong programming skills in at least one production language, with the ability to read and review code across the AI stack.

Location

• Durham, United States
• Miami, United States
• Palo Alto, United States
• Washington DC, United States

Our Benefits

• Opportunity of earning equity at Nu
• Medical Insurance
• Dental and Vision Insurance
• Life Insurance and AD&D
• Extended maternity and paternity leaves 
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• NuCare - Our mental health and wellness assistance program
• 401K
• Saving Plans - Health Saving Account and Flexible Spending Account
• Work-from-home Allowance
• Relocation Assistance Package, if applicable.

Work Model for this Role

Hybrid 2–3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Location-Specific Disclosures

• Palo Alto: Total compensation includes base salary, RSUs and benefits. Base salary range: $15,360 - $23,040

AI at Brex

AI Engineering at Brex is redefining how businesses run their finances by building intelligent, autonomous systems directly into the Brex platform. Our teams develop AI agents that don’t just surface insights—they take action, optimizing spend, managing workflows, and making real-time decisions on behalf of our customers. By deeply integrating proprietary financial data with product and platform infrastructure, we’re turning complex financial operations into simple, automated experiences and setting a new standard for how modern finance works.

What you’ll do

You’ll own Brex’s simulation and validation platform for AI-powered products. Your mandate is simple and unforgiving: ensure that every AI surface at Brex is continuously scrutinized under extreme, realistic conditions — and that teams can ship with confidence because of it.

You’ll build a system that uses synthetic data and scenario generation as a recursive self-improvement loop. Product teams will rely on it to catch regressions before customers do, to validate new capabilities safely, and to evolve prompts and agent behavior continuously. This platform will run against isolated, ephemeral environments that mirror production closely enough to matter.

This is not a research role. It’s about exercising real products, breaking them creatively, and forcing the organization to get better.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We require three coordinated days in the office per week — Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Evolve and scale a simulation and validation platform to continuously stress-test Brex’s AI products using large-scale synthetic data.
• Develop evaluation mechanisms to detect regressions, edge cases, and failure modes in non-deterministic systems prior to customer impact.
• Run continuous testing in isolated, production-like environments and set quality gates, including authority to block launches when standards are not met.
• Partner closely with product engineering teams to improve system testability, isolation, and overall robustness.
• Define and uphold company-wide standards for AI feature quality, using simulation-driven insights to guide prompt and system evolution, while driving the technical bar for a small, high-impact team.

Requirements

• Experience building and owning complex software systems where correctness, reliability, and failure modes are critical.
• Experience designing test, simulation, or validation systems for non-deterministic or high-stakes environments.
• Strong systems thinking, with the ability to decompose complex problems and reduce incidental complexity.
• Demonstrated ability to influence product architecture through quality, reliability, and launch-readiness constraints.
• Comfort operating with real authority and cross-team influence, including blocking launches and partnering across seniority levels to raise the quality bar.

Bonus points

• Previous experience on simulation or testing of inherently complex systems (AI/ML, distributed systems, robotics, IoT, medical devices, aerospace, defense, etc.).
• Experience building internal platforms that became critical shared infrastructure.
• Strong intuition for failure modes in real-world systems.

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

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

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. 

The work: 

Key Responsibilities:

Build AI that matters. We ship production GenAI apps for confidential federal programs across defense, national security, public safety, civilian, and military health where reliability, privacy, and safety aren’t optional. AFS is a technology company within global Accenture and a Glassdoor Top 100 Best Place to Work. You’ll join a collaborative, inclusive community with handson growth, certifications, and industry training. We ship in weeks, not quarters, and measure success with latency, reliability, safety, and cost. 

Confidentiality matters: We don’t disclose program details publicly. If you advance, we’ll share specifics during the process. 

Role Overview 

You’ll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You’ll own the end-to-end path from use case evaluation → production deployment → operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale. 

What You’ll Do (Day to Day) 

• Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost. 

• Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies. 

• Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma). 

• LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback. 

• RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise. 

• Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails. 

• SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend. 

• Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects. 

• Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls. 

You'll Thrive Here If you have 

• End-to-end ownership of production systems: integration → deployment → observability → incident response. 

• Hands-on experience with LLMs, transformer based apps, and RAG in production. 

• Strong Python 

• Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data. 

• U.S. Citizenship 

Nice to Have 

• Integration with leading cloud AI services or on prem inference stacks  

• Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops. 

• Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance. 

• Experience implementing tool using agents for API integration and external data access. 

• Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell). 

• Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping. 

• Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude). 

• Contributions to internal frameworks or opensource; mentorship of engineers. 

• Clear communication with engineers, PMs, and security/compliance stakeholders. 

We are entering a new chapter in technology - one shaped by a generalization of AI. Accenture is a trusted industry leader at the forefront of AI innovation, providing clients with scalable AI and generative AI solutions for reinvention - to solve new problems, create new inventions, change how we work and live, and transform industries and governments.   

Seeking a Generative AI Engineer with the technical acumen and problem-solving ability to identify and develop new opportunities for the use of AI agents to solve real-world mission-critical problems for our clients. You will have expertise in the key components to power GenAI adoption - including rapid prototyping of custom applications, search capabilities such as R.A.G, Prompt Engineering Expertise, Large Language Model Expertise (Selection, fine tuning, and deployment) and GenAI Use Case evaluation. You will collaborate with a community of GenAI leaders, software and systems engineers, data scientists, solutions architects, and product owners to deliver innovative world-class solutions that will transform our clients ecosystem and reinvent the way they operate. 

The Work: 

• Design and build GenAI use cases based on client's needs and specific data    

• Understanding of Agentic AI frameworks and design and when they are appropriate for use 

• Develop and deploy generative AI models using platforms such as Amazon Kendra, Google Vertex AI, and AWS Bedrock. 

• Implement large language models (LLMs) and transformer models to create advanced AI applications. 

• Integrate solutions with cloud-based AI services such as Google Cloud Document AI, Google Cloud Gemini, Google Cloud Gemma, and Google Cloud Generative AI Language Models. 

• Utilize NVIDIA AI Foundations and OpenAI ChatGPT to develop and refine AI applications. 

• Leverage Databricks LLM and Databricks Mosaic AI for data analysis and AI model development. 

• Show your curiosity, motivation, and passion for experimentation and continuous learning to drive AI innovation that is applicable across enterprise client domains. 

Here's what you need: 

• Experience working with modern generative AI capabilities including large language models, transformer models, and retrieval-augmented generation 

• Expertise in AI platforms (e.g., Amazon Kendra, Google Vertex AI, AWS Bedrock, and Azure AI, etc.) 

• Experience with Google Cloud services (e.g., Document AI, Gemini, Gemma, Generative AI Language Models) 

• Experience building RAG systems with vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS) 

• Experience using modern software languages (e.g., Python, SQL, Go) to develop generative AI solutions  

Bonus points if you have: 

• Strong understanding of AI ethics, responsible AI, and generative AI data ethics. 

• Experience in LLM fine-tuning and LLMOps. 

• Ability to author and validate prompts for AI models. 

• Familiarity with NVIDIA AI Foundations and OpenAI ChatGPT. 

• Experience with AI-assisted development platforms (e.g., Cursor, Windsurf, Claude, etc.). 

• Experience implementing tool-using AI agents to assist in API integration - enabling agent access to external data sources and web services. 

• Experience using deployment/virtualization tools in containerized environments (e.g., VMware, Docker, Kubernetes) 

• Proficiency in scripting with Linux Bash, PowerShell, or equivalent automation tools 

Security Clearance:

• Active Top Secret or TS/SCI or TS/SCI with polygraph clearance

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease, and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working, and playing remarkable - giving us back our most valuable asset, time.

Who you are

Metropolis is seeking a Staff Software Engineer to join our Revenue Platform team. In this role, you will own the technical direction for our billing, payments, and invoicing infrastructure, charting the course for a system that already processes tens of millions in monthly transactions. You will balance immediate business needs with long-term architectural improvements, identifying high-impact enhancements and designing practical migration strategies to support our rapid growth.

As a technical leader, you will partner closely with engineering, finance, and operations teams to solve complex challenges involving pricing rules, subscription billing, and enterprise invoicing. You are a systems thinker who enjoys understanding how things work and building the roadmaps that improve a platform while it runs. Your work will directly shape how Metropolis monetizes its platform and expands into new verticals beyond parking, ensuring our financial systems remain resilient, compliant, and remarkably efficient.

What you’ll do

• Own the technical architecture and evolution of Metropolis's billing, payments, and invoicing systems, establishing standards for financial accuracy, transaction integrity, and compliance that ensure every dollar is correctly captured and accounted for
• Design and implement resilient payment processing with support for multiple payment gateways (Stripe,  etc.), intelligent routing between processors, retry strategies for failed transactions, and graceful handling of partial failures to maximize payment success rates
• Build comprehensive monitoring and reporting for revenue operations, including payment success rates, billing accuracy metrics, reconciliation dashboards, failed transaction alerts, and audit trails that provide visibility from customer transactions to accounting close
• Partner with finance and operations teams on payment failures, billing disputes, refund workflows, and reconciliation issues – building tools and automation that reduce manual intervention and improve mean time to resolution for customer-impacting revenue issues
• Drive adoption of revenue system best practices across services, including idempotent payment processing, distributed transaction handling, compensation workflows for failures, audit logging, and testing strategies that ensure financial correctness
• Own integrations with external systems, including payment gateways, ERP, data analytics, etc., ensuring reliable data flow and maintaining compliance requirements across the revenue stack

What we’re looking for

• 8+ years of hands-on engineering experience with a focus on building revenue systems like payment platforms
• Strong systems thinking for financial correctness with proven ability to design distributed revenue systems that handle edge cases gracefully: partial failures, duplicate requests, timing issues, currency conversion, tax calculation, and maintaining transaction integrity across service boundaries
• Database and financial data expertise, including transaction isolation, audit logging, point-in-time recovery, handling financial data migrations, and experience with systems that require both high availability and absolute correctness
• Payment gateway and integration experience with production knowledge of Stripe, PayPal, or similar processors; tax calculation services; accounting system integrations; and the operational reality of depending on external financial services, including compliance requirements like PCI-DSS
• Excellent technical communication with the ability to influence technical decisions across teams (particularly finance, accounting, and data teams), document complex systems, conduct post-mortems, and establish reliability standards organization-wide
• Experience with sophisticated usage of rapidly developing AI-assisted development skills in real-world codebases, including fluent use of Claude Code/GPT Codex/Windsurf or similar tools in multi-agent mode, spec-driven development (SDD),  MCP/skills optimization, context/prompt engineering
• Local to the Seattle area

While not required, these are a plus

• BS or MS in Computer Science or a relevant engineering discipline
• Expert-level revenue systems engineering with hands-on experience building billing platforms, payment processing pipelines, reconciliation systems, and handling challenges like idempotent transactions, failed payment retries, proration logic, multi-currency support, and revenue recognition – you've seen these problems before and know the patterns that work
• Expert revenue systems engineering with hands-on experience building billing platforms, payment processing, reconciliation, and managing complex challenges like idempotent transactions, payment retries, proration, multi-currency support, and revenue recognition.
• Financial systems expertise with deep experience implementing audit trails, reconciliation workflows, revenue reporting, and compliance controls at scale – you understand what it takes to maintain penny-perfect accuracy
• Java expertise with a deep understanding of JVM performance, concurrency, and operational characteristics. Scala experience is a big plus
• Experience with AI-powered development tools such as Claude Code, GitHub Copilot, or similar agentic coding tools for enhanced productivity

  Our Stack

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

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

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $220,000 USD to $250,000 USD annually. The actual base pay offered is determined by several variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more.

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 federal civilian (and, occasionally, state and local) 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 government 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.

Core 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 federal government 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.

• Travel frequently (25-50%) to customer sites to build in person with customers.

• Be a champion for Anthropic’s mission in the field.

You Might Be a Good Fit If You Have:

• Security clearance not required, but a plus

• Must have prior experience working with US federal civilian, state, or local agencies 

• 4+ 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.

• Experience with government IT systems and/or AI deployment patterns is a plus.

ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You'll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won't just contribute. You'll make things happen—fast.

The Opportunity

ZoomInfo has rebuilt around AI. We have the orchestration infrastructure, the tools platform, the intelligence layer. Now we need someone to turn that infrastructure into outcomes—someone who lives at the intersection of what's technically possible and what GTM teams actually need.

This role owns the agentic ecosystem: the core agents that power ZoomInfo's products, the Plays library that packages intelligence into deployable workflows, and the marketplace where customers discover, customize, and deploy automation. You'll build agents that book meetings, enrich pipelines, resurrect dead leads, and orchestrate multi-step GTM motions. Then you'll package them into Plays that non-technical users can deploy in clicks, not code.

You're not managing from the sidelines. You're building. You'll work in our Plays builder the way a RevOps leader works in their automation tools—hands-on, iterative, constantly shipping. You'll prototype agents, refine prompts, test orchestration patterns, and validate that what we build actually moves pipeline. When you identify a gap in what our agents can do, you'll partner with the tools and infrastructure teams to close it.

The marketplace you own is how ZoomInfo's agentic capabilities reach the world. Internal teams deploy your Plays across Copilot, GTM Studio, and MarketingOS. Customers browse, customize, and activate automation from your library. Partners and developers connect through MCP gateways you define. Every surface where ZoomInfo's agentic intelligence becomes accessible—you own it.

This is a rare role: part builder, part GTM strategist, part platform owner. You need to understand how SDR teams actually prospect, how marketing ops builds nurture flows, how CS teams identify expansion signals. Then you need to translate that understanding into agents and Plays that work reliably at scale. The infrastructure exists. The data exists. We need someone to turn it into the workflows that transform how GTM teams operate.

What You'll Do

Build Core Agents & Plays Design, build, and iterate on the agents and Plays that ship inside ZoomInfo's products. You'll work at multiple levels of abstraction: building agents from primitives when novel capabilities require it, composing existing agents into complex orchestrations, and packaging everything into Plays that non-technical users can deploy. This isn't spec-writing—you'll build in our Plays environment daily, testing what works and shipping what delivers.

Own the Plays Library Curate and expand ZoomInfo's library of pre-built GTM workflows. Identify high-value use cases through customer research, competitive analysis, and GTM intuition. Prioritize which Plays to build, define their logic and orchestration, validate they deliver measurable outcomes, and iterate based on adoption and performance data. The library is the product—its breadth, quality, and relevance determine whether customers see ZoomInfo as a data vendor or an automation platform.

Define the Marketplace Experience Own the customer-facing marketplace where users discover, evaluate, and deploy agentic workflows. Define the information architecture, discovery mechanisms, and activation flows that help users find the right Play for their use case. Balance curation with abundance—enough options to address diverse needs, enough guidance to prevent paralysis. Measure success through activation rates, time-to-value, and Play retention.

Translate GTM Expertise into Agentic Design The best agents encode deep understanding of the workflows they automate. Bring GTM operational expertise to agent design: How do top SDRs actually research accounts? What signals trigger effective outreach timing? How do marketing ops teams think about lead routing? Translate this knowledge into agent behaviors, Play logic, and orchestration patterns that feel like they were built by someone who's lived in RevOps.

Close the Loop with Platform Teams You're the voice of "what agents need to do" speaking to the teams building "what agents can do." When you discover that a critical GTM workflow requires a capability that doesn't exist, partner with the tools and infrastructure teams to prioritize it. When platform improvements unlock new possibilities, translate them into Plays that demonstrate value. You're the bridge between infrastructure leverage and customer outcomes.

What You'll Bring

• 6-15 years product management experience with 2+ years focused on GTM technology, workflow automation, or AI-powered products
• Direct experience building agentic workflows—you've shipped automation using tools like Relevance.ai, Lindy.ai, n8n, or similar no-code/low-code agent builders
• Hands-on familiarity with AI-assisted development (Claude Code, Cursor, or similar)—you prototype and build, not just specify
• Deep understanding of GTM operations: how sales, marketing, and success teams actually work, the tools they use, the metrics they track, the workflows they build
• Experience with complex workflow orchestration—multi-step, multi-system automation with branching logic, error handling, and human-in-the-loop patterns
• Track record shipping products where you personally built significant portions of the experience, not just managed engineers building it

Who You Are

Builder First You don't just write requirements—you build. You're comfortable in no-code workflow builders, and you reach for Claude Code or Cursor when you need to go deeper. You prototype to learn, ship to validate, and iterate based on what you discover. Your PRDs include artifacts you've built, not just wireframes someone else will implement.

GTM Operations Native You've lived in the world your users inhabit. You've built sequences in Outreach or Salesloft. You've configured lead routing in Salesforce or HubSpot. You've debugged why a Marketo program isn't firing. You understand the gap between how GTM workflows should work and how they actually work—the edge cases, the data quality issues, the human workarounds. This knowledge shapes every agent you design.

Agentic Workflow Intuition You understand what makes agents succeed or fail. You know how to write tool descriptions that guide reliable invocation. You've debugged orchestration flows where agents took unexpected paths. You think about failure modes, human oversight, and graceful degradation. You can look at a complex workflow and identify where it will break—then design around it.

Marketplace Product Sense You've thought about discovery, curation, and activation at scale. You understand that a library of 500 Plays is worthless if users can't find the right one. You think about information architecture, progressive disclosure, and the journey from "browsing" to "deployed and delivering value." You balance flexibility with guidance.

Customer Empathy with Technical Depth You can sit with a VP of Sales and understand their pipeline challenges, then translate that into agent specifications an ML engineer can build. You move fluidly between "we need to accelerate deal velocity" and "the agent needs to invoke the CRM lookup tool before the enrichment tool to avoid redundant API calls." You don't choose between business context and technical precision—you hold both.

Intellectual Curiosity The agentic landscape evolves weekly. You follow what's shipping—new agent frameworks, orchestration patterns, MCP developments, prompt engineering techniques. You try new tools not because it's your job but because you're genuinely curious about what's possible. You bring external learnings back to the team and challenge assumptions when better approaches emerge.

#LI-VC1

#LI-Hybrid

About the role

We're hiring a Tech Lead for DevOps to own the delivery and operational health of our platform engineering team. This is a hands-on leadership role: you carry significant engineering weight alongside the team while owning the operating rhythm, sprint commitments, and accountability for what ships.

You will work in close partnership with our Cloud Architect, who owns platform strategy and technology standards. Your job is to translate that direction into a clear, well-organized backlog: and then drive the team to deliver it with quality and predictability. You are the bridge between strategic direction and team execution.

We build in an AI-forward environment. You'll be expected to leverage AI tools in your own work and create the conditions — in pipelines, tooling, and team culture — for engineers to do the same effectively and responsibly.

What you'll do

Delivery ownership

• Set and own team priorities: determine what the team works on, in what order, and why; translate VP direction and Cloud Architect input into a clear, executable backlog
• Own sprint commitments and team capacity planning: accountable for what the team commits to and whether it ships
• Surface risks early and communicate delivery status accurately to the VP
• Run sprint ceremonies: planning, stand-ups, retros, and demos
• Maintain Jira hygiene: tickets are well-defined, updated, and always reflect actual state
• Identify and resolve blockers before they slow the team down
• Communicate cross-team dependencies early and proactively

Technical execution

• Be a strong technical contributor: carry significant engineering weight alongside the team and actively deliver on high-impact work
• Own day-to-day technical decisions within the team's scope
• Translate architectural direction into sprint-level tasks the team can act on
• Build and evolve CI/CD pipelines and delivery automation: ensuring deployment safety, consistency, and velocity
• Improve observability and operational readiness across metrics, logging, distributed tracing, and alerting (Prometheus, Grafana, Dynatrace, Elasticsearch), including actionable dashboards and SLO-based alerting
• Design and implement automation and self-service workflows using infrastructure-as-code, APIs, and developer platforms to reduce developer friction
• Implement secure delivery practices with policy-driven pipeline controls
• Contribute to infrastructure in Terraform, working within established architectural patterns and standards
• Support and improve secrets management patterns across runtime and CI/CD workflows
• Champion AI-assisted development practices across the team: prompt engineering workflows, AI-powered code review, and tooling integrations (e.g., GitHub Copilot, Cursor, or equivalent) as first-class parts of the engineering workflow

Operational readiness

• Own incident response coordination: drive the process, communicate status, and ensure issues reach the right people
• Participate in the on-call rotation and help drive improvements that reduce incidents and alert noise over time
• Build and maintain operational runbooks, escalation paths, and documentation for team-owned systems
• Drive production readiness as a continuous standard, not a one-time checklist

People management & team development

• Manage a team of engineers: this is a formal people manager role with full accountability for the team's performance and growth
• Own performance management: regular 1:1s, performance reviews, and direct, constructive feedback
• Own career development: growth planning, identifying opportunities, and building engineer capability over time
• Mentor engineers through code reviews, pairing, and delivery coaching
• Build a team culture that is organized, reliable, and focused on impact
• Manage team working norms, address blockers, and partner with the VP on people concerns that require escalation

About you

• 7+ years of hands-on experience in cloud infrastructure, DevOps, SRE, or platform engineering
• Demonstrated experience as a formal people manager or tech lead with direct reports: including performance management, career development, and building team capability
• Demonstrated experience leading technical delivery: owning timelines, driving sprint execution, and being accountable for what a team ships
• Ability to translate high-level technical direction into well-scoped, executable team work
• Comfort partnering with senior technical peers (Cloud Architect, VP) and sound judgment on when to consult vs. decide independently
• Strong hands-on experience with Terraform in production (modules, patterns, environment strategy, state management)
• Strong hands-on experience operating Kubernetes in production (EKS strongly preferred)
• Strong AWS fundamentals: practical experience with compute, networking, IAM, and production operations
• Experience building and maintaining CI/CD pipelines (GitLab CI preferred; GitHub Actions transferable)
• Strong observability fundamentals including metrics, logging, distributed tracing, SLO/SLI design, and alerting strategy: with experience evaluating and evolving observability practices at a platform level
• Experience building automation using Bash and a general-purpose language (Go or Python)
• Strong troubleshooting skills: you drive root cause analysis and implement long-term fixes
• Hands-on experience using AI coding tools (e.g., GitHub Copilot, Cursor, Claude) as a productivity multiplier in production engineering work
• Location Requirement: This position requires regular in-person attendance at one of our two office locations (Richmond, VA or Arlington, VA). Candidates must already be located within a commutable distance to either location, as relocation assistance is not available at this time.

Preferred qualifications

• Experience with Istio or other service mesh technologies
• Experience operating relational databases in AWS (RDS PostgreSQL/Aurora/MS SQL)
• Experience with AWS Lambda or serverless architectures
• Experience improving reliability for distributed systems at scale
• Prior experience as a technical anchor or team lead in a platform or infrastructure context
• Experience building or operating infrastructure that supports AI/ML workloads (compute, storage, serving patterns) in AWS

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.

You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.

• Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
• Direct the orchestration of asynchronous agent fleets to meet mission requirements.
• Lead customer engagements to translate mission needs into technical requirements.
• Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
• Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
• Drive the platform roadmap by providing technical specifications for Federal product offerings.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders.

You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency.

• Define technical strategy for agentic guardrails, explainability, and fleet orchestration.
• Ensure system reliability and performance across multiple security classifications and network types.
• Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance.
• Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members.
• Influence the long-term product strategy and technical roadmap for the Federal business unit.
• Consult on the architecture of AI-powered solutions for large-scale federal contracts.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

About the Role: 

The AI Engineer will help define, architect, and implement / project manage how artificial intelligence is applied across Planet's marketing organization to improve efficiency, scalability, and performance. This role will identify opportunities to integrate AI into marketing workflows, campaign development, and marketing operations, while helping build the technical infrastructure in tandem with the corporate engineering team that powers pipeline generation and customer acquisition.

This person will work cross-functionally with Growth Marketing, Marketing Operations, Revenue Operations, Product Marketing, Corporate Engineering, and Data teams to introduce AI-driven systems and automated agents that improve campaign velocity, marketing insights, and pipeline impact. The ideal candidate is a builder at heart who combines marketing and revenue operations knowledge with a technical mindset to help translate emerging AI capabilities and business needs into scalable GTM systems.

Impact You'll Own:

• Identify gaps, create strategy for, and implement AI across marketing workflows including campaign execution, content production, analytics, and marketing operations. From concept, through execution. 
• Architect and build an AI-first GTM engine that identifies, engages, and converts high-value customer segments through automated lead research and qualification systems.
• Use AI to spearhead complex data analytics and build GTM data optimization layers to report on funnel performance and revenue attribution.
• Partner with Growth and regional marketing teams to apply AI to campaign planning, structured messaging experimentation loops, and audience targeting.
• Collaborate with Marketing Operations, RevOps, and Corporate Engineering to integrate new AI tools and automated outreach sequences into existing CRM and marketing automation platforms.
• Work with Corporate engineering to evaluate emerging AI technologies and vendors, selecting tools that build a robust GTM technology stack.
• Develop internal playbooks and frameworks for how marketing teams should use AI tools in their daily work.
• Support AI-driven experimentation including creative testing, automated messaging variations, and landing page drafts.
• Help train marketing teams on AI capabilities, best practices, and responsible use of AI technologies.
• Lead, monitor, and report on the impact of AI initiatives across campaign velocity, marketing efficiency, and pipeline generation.
• Work closely with cross-functional teams to ensure AI initiatives align with Planet's mission to make global change visible, accessible, and actionable.

What You Bring:

• 5+ years of experience in software engineering, data analytics, or automation engineer with at least 1 year building production-grade AI systems.
• Hands-on experience working with LLMs (OpenAI, Anthropic, open-source), including prompt design, evaluation, and iteration
• Experience building agentic workflows that take actions (not just generate text), including tool use, chaining, and structured outputs
• Demonstrated ability to design and build complex operational systems from scratch that support marketing, sales, or revenue teams.
• Experience working in marketing technology platforms such as CRM systems (Salesforce), marketing automation tools (Marketo), and data enrichment platforms.
• Experience implementing artificial intelligence tools including generative AI, workflow orchestration tools, and AI-powered analytics platforms.
• Experience improving marketing workflows through automation, process design, or technical system implementation.
• Ability to translate technical capabilities into practical marketing applications and automated engagement sequences that support business goals.
• Experience working cross-functionally with marketing, operations, product, corporate engineering, and data teams.
• Strong analytical thinking and the ability to interpret market data and customer signals to evaluate the impact of marketing initiatives.
• Excellent communication skills and the ability to help teams adopt new tools and processes.
• Comfort operating in ambiguous, fast-moving environments where systems and processes are being built for the first time.

What Makes You Stand Out: 

• Experience applying AI to marketing functions such as campaign development, content production, experimentation, or personalization, reporting, analytics, and personalization. 
• You’ve built AI systems that directly impacted revenue, growth, or operations (not just demos or prototypes)
• Familiarity with marketing AI tools such as generative content platforms, AI analytics tools, or AI-native GTM enhancements.
• Experience building internal frameworks or playbooks for new technology adoption.
• Experience working in high-growth technology companies or data-driven marketing environments.
• Strong technical curiosity regarding how automation and AI can reshape traditional revenue workflows.

Application Deadline: July 14, 2026

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

• Comprehensive Medical, Dental, and Vision plans
• Health Savings Account (HSA) with a company contribution
• Generous Paid Time Off in addition to holidays and company-wide days off 
• 16 Weeks of Paid Parental Leave
• Wellness Program and Employee Assistance Program (EAP)
• Home Office Reimbursement
• Monthly Phone and Internet Reimbursement
• Tuition Reimbursement and access to LinkedIn Learning
• Equity
• Commuter Benefits (if local to an office)
• Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below.  Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location.  The range displays our typical hiring range for new hire salaries in US locations only.  Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

About the Role: 

The AI Engineer will help define, architect, and implement / project manage how artificial intelligence is applied across Planet's marketing organization to improve efficiency, scalability, and performance. This role will identify opportunities to integrate AI into marketing workflows, campaign development, and marketing operations, while helping build the technical infrastructure in tandem with the corporate engineering team that powers pipeline generation and customer acquisition.

This person will work cross-functionally with Growth Marketing, Marketing Operations, Revenue Operations, Product Marketing, Corporate Engineering, and Data teams to introduce AI-driven systems and automated agents that improve campaign velocity, marketing insights, and pipeline impact. The ideal candidate is a builder at heart who combines marketing and revenue operations knowledge with a technical mindset to help translate emerging AI capabilities and business needs into scalable GTM systems.

Impact You'll Own:

• Identify gaps, create strategy for, and implement AI across marketing workflows including campaign execution, content production, analytics, and marketing operations. From concept, through execution. 
• Architect and build an AI-first GTM engine that identifies, engages, and converts high-value customer segments through automated lead research and qualification systems.
• Use AI to spearhead complex data analytics and build GTM data optimization layers to report on funnel performance and revenue attribution.
• Partner with Growth and regional marketing teams to apply AI to campaign planning, structured messaging experimentation loops, and audience targeting.
• Collaborate with Marketing Operations, RevOps, and Corporate Engineering to integrate new AI tools and automated outreach sequences into existing CRM and marketing automation platforms.
• Work with Corporate engineering to evaluate emerging AI technologies and vendors, selecting tools that build a robust GTM technology stack.
• Develop internal playbooks and frameworks for how marketing teams should use AI tools in their daily work.
• Support AI-driven experimentation including creative testing, automated messaging variations, and landing page drafts.
• Help train marketing teams on AI capabilities, best practices, and responsible use of AI technologies.
• Lead, monitor, and report on the impact of AI initiatives across campaign velocity, marketing efficiency, and pipeline generation.
• Work closely with cross-functional teams to ensure AI initiatives align with Planet's mission to make global change visible, accessible, and actionable.

What You Bring:

• 5+ years of experience in software engineering, data analytics, or automation engineer with at least 1 year building production-grade AI systems.
• Hands-on experience working with LLMs (OpenAI, Anthropic, open-source), including prompt design, evaluation, and iteration
• Experience building agentic workflows that take actions (not just generate text), including tool use, chaining, and structured outputs
• Demonstrated ability to design and build complex operational systems from scratch that support marketing, sales, or revenue teams.
• Experience working in marketing technology platforms such as CRM systems (Salesforce), marketing automation tools (Marketo), and data enrichment platforms.
• Experience implementing artificial intelligence tools including generative AI, workflow orchestration tools, and AI-powered analytics platforms.
• Experience improving marketing workflows through automation, process design, or technical system implementation.
• Ability to translate technical capabilities into practical marketing applications and automated engagement sequences that support business goals.
• Experience working cross-functionally with marketing, operations, product, corporate engineering, and data teams.
• Strong analytical thinking and the ability to interpret market data and customer signals to evaluate the impact of marketing initiatives.
• Excellent communication skills and the ability to help teams adopt new tools and processes.
• Comfort operating in ambiguous, fast-moving environments where systems and processes are being built for the first time.

What Makes You Stand Out: 

• Experience applying AI to marketing functions such as campaign development, content production, experimentation, or personalization, reporting, analytics, and personalization. 
• You’ve built AI systems that directly impacted revenue, growth, or operations (not just demos or prototypes)
• Familiarity with marketing AI tools such as generative content platforms, AI analytics tools, or AI-native GTM enhancements.
• Experience building internal frameworks or playbooks for new technology adoption.
• Experience working in high-growth technology companies or data-driven marketing environments.
• Strong technical curiosity regarding how automation and AI can reshape traditional revenue workflows.

Application Deadline: July 14, 2026

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

• Comprehensive Medical, Dental, and Vision plans
• Health Savings Account (HSA) with a company contribution
• Generous Paid Time Off in addition to holidays and company-wide days off 
• 16 Weeks of Paid Parental Leave
• Wellness Program and Employee Assistance Program (EAP)
• Home Office Reimbursement
• Monthly Phone and Internet Reimbursement
• Tuition Reimbursement and access to LinkedIn Learning
• Equity
• Commuter Benefits (if local to an office)
• Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below.  Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location.  The range displays our typical hiring range for new hire salaries in US locations only.  Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

AI Software Engineer – Cloud AI Platforms

At NICE, we are not just building software—we are transforming how cloud operations are run using AI. We are building intelligent platforms that can understand system behavior, make decisions, and automate real-world operational workflows at scale. If you’re excited about applying AI beyond chatbots into real production systems, this is an opportunity to work on meaningful, high-impact problems.

What’s the role all about?

As an AI Software Engineer, you will be part of a team building AI-powered operational platforms that integrate across monitoring systems, CI/CD pipelines, ticketing tools, and cloud infrastructure. You will work on designing and implementing intelligent workflows, integrating AI models, and building scalable systems that automate complex operational tasks.

This is a highly hands-on role focused on building, integrating, and scaling AI-driven solutions in production environments.

How will you make an impact?

• Build and scale AI-driven workflows and automation systems
• Develop integrations with systems like monitoring platforms, ticketing tools (ServiceNow, Jira, OpsGenie), CI/CD pipelines, and cloud services
• Design and implement APIs, tools, and data pipelines that power AI-driven decision-making
• Work on LLM integrations, prompt engineering, and orchestration layers — streaming responses, function calling, tool use, RAG pipelines, agentic orchestration
• Build and maintain full-stack AI applications using TypeScript, React, and Next.js — from user dashboards and personalized experiences to real-time analytics and interactive tools
• Translate real-world operational problems into automated, intelligent solutions
• Collaborate with Product, SRE, and Infrastructure teams to deliver end-to-end capabilities
• Improve system performance, reliability, and observability
• Build evaluation and observability systems — measure model capabilities, monitor output quality, and create dashboards that keep the product improvable
• Create reusable platforms and tools that accelerate development — component libraries, shared abstractions, internal tooling that multiplies team productivity

Key Responsibilities

• Design and develop scalable backend systems for AI-powered platforms
• Build and maintain AI integrations, workflows, and automation pipelines
• Implement REST APIs, microservices, and event-driven architectures
• Design and implement database schemas and queries for complex domains — tracking, engagement, reporting
• Work with both structured and unstructured data for AI use cases
• Contribute to CI/CD pipelines, testing, and deployment automation
• Troubleshoot and optimize production systems
• Collaborate with cross-functional teams to deliver high-quality solutions
• Contribute to reusable frameworks and engineering best practices
• Prototype fast — move from concept to working demo in days, ship incrementally

What we’re looking for

• 5+ years of software engineering experience, strong focus on full-stack web development
• Expert in TypeScript and React — performance optimization, modern patterns (hooks, context, suspense), component architecture
• Production experience with Next.js — App Router, Server Components, API routes, SSR/SSG, edge deployment
• Hands-on experience with LLMs — prompt engineering, streaming APIs, function calling, tool-use, chaining and orchestration patterns
• Experience with Vercel AI SDK — unified LLM provider interface, streaming, structured output, tool calling across OpenAI/Anthropic/Google/xAI
• Model Context Protocol (MCP) — building or consuming MCP servers for extensible AI tool use
• Strong backend fundamentals — Node.js or Python, REST/GraphQL APIs, relational databases, Redis, auth
• Solid database design — PostgreSQL, Drizzle ORM, schema modeling for complex domains, query optimization, migrations
• Experience building scalable, distributed systems in cloud environments (AWS / Azure)
• Working knowledge of CI/CD, Docker, Kubernetes
• Familiarity with Tailwind CSS, Radix UI and modern component-driven UI development
• High agency — you operate independently in ambiguous environments, take ownership of problems, and drive them to completion
• Strong problem-solving and analytical skills
• Ability to work in a fast-paced, evolving environment
• Communicate effectively with both technical and non-technical stakeholders

Nice to have

• Experience building agentic coding tools, AI agent frameworks, or developer-facing SDKs/APIs (Claude Agent SDK, OpenAI Agents SDK)
• Experience with Vercel ecosystem — Next.js, AI SDK providers, Turbopack
• Background in evaluation frameworks — measuring model capabilities, collecting human feedback at scale, A/B testing outputs
• Experience with sandboxed execution environments for safely running AI-generated code
• Built research tools, experimentation platforms, or scientific software
• Proficiency with Python — FastAPI/Django, data pipelines, ML tooling
• Knowledge of observability tools (Grafana, Prometheus, Sentry, etc.)
• Experience building automation or internal platforms
• Familiarity with real-time features — WebSockets, streaming UX, collaborative interfaces
• Knowledge of advanced web technologies — WebGL, WebAssembly, web workers, PWAs
• Experience with alternate JS runtimes — Bun, Deno
• Built open-source tools or platforms with active user communities
• Strong quantitative foundation (math, physics, or related fields)

Representative Projects

Things you might build in this role:

• Interfaces for collecting and managing human feedback on model outputs at scale
• Experiment orchestration platforms — launch, monitor, and analyze complex AI research runs
• Visualization tools that help understand model behavior and identify failure modes
• Reusable components and frameworks that enable rapid development of new AI applications
• Sandboxed execution environments for safely running AI-generated code
• AI-powered personalization engines — tutoring, content generation, adaptive features
• Workflow builders that let non-engineers orchestrate AI capabilities visually
• Enterprise integrations — ServiceNow, Salesforce, Confluence, Jira

Data Scientist 

Location: Woodinville, WA

Details: Hybrid 

Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value.   

We are looking for a versatile AI/ML Engineer who can lead, sell, design, and implement modern architecture for a diverse set of customers and industries. The ideal candidate would have deep experience in designing high-value advanced analytics solutions utilizing popular analytical frameworks running on Azure, GCP, and AWS. This position will be responsible for leading customer conversations, creating and presenting project architecture, and leading delivery.

Primary responsibilities include mentoring and leading other consultants, leading pre-sales workshops with finance and technology executives to uncover innovative ways to apply advanced analytics techniques to solve business problems in new ways. The role can be hands-on when necessary but should have Direct delivery experience to recommend technologies, solutions, and help troubleshoot.    

Responsibilities: 

• Drive growth through business development, resourcing, and quality delivery. 

• Monitor business impact and value generation of analytics projects. 

• Help create go-to-market strategies around advanced AI/ML Services and hardware. 

• This role will be directly involved in the business development process, delivering customer demos to show the value of how data can drive business goals. 

• Create proposals and SOWs. 

• Work closely with sales and other practice leaders to recommend strategies to grow our data science services. 

• Manage full sales cycles, end-to-end, for high potential clients. 

• Evaluate business impact and priority initiatives for our portfolio of managed analytics customers.  

• Talent Leadership and Product Ownership. 

• Help with planning and staffing for data science projects. 

• Provide support for project managers through developing tasks, estimates, and dependencies to meet expectations. 

• Train the data science team on best practices and new technology initiatives.  

• Anticipate the impact of new technologies and frameworks and help create compelling data science offerings to our clients. 

Skills you bring with you: 

• Knowledge of how to use data science/AI/ML techniques in operations to impact corporate financials.  

• Working knowledge of DevOps process (CI/CD) applied to data science and ML ops. 

Qualifications: 

• Bachelor’s or Master’s Degree in Advanced Math, Data Science, or Computer Science.  

• 5-8+ years of experience with advanced data science techniques, frameworks, libraries, and technologies including but not limited to: 

• Tensorflow, KubeFlow, Python, R, Keras, NumPY, SciKit, PyTorch, SQL.
  
  
• Azure ML, Vertex AI, SageMaker, Databricks, Big query/Redshift/Snowflake
  
  
• ELT/ELT/Pipeline Design, Data Modeling, Spark, Airflow/DBT and API Integration Patterns

Nice to have: 

• LLM’s, RAG, Vector Databases, Prompt Evaluation, GenAI Solution Patterns 

The base salary range for this full-time position in the US is $130,000 - $140,000 annually + bonuses + benefits.  Redapt salary ranges are determined by role, level, and location.  The salary range displayed in each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations.  Please note, the base pay offered may vary within the range depending on a wide array of factors including but not limited to work location, job related knowledge/skills, relevant education/training, and level of experience.  Please note that the compensation details listed in the US role postings reflect the base salary only, and do not include bonuses or benefits. 

Equal Employment Opportunity: 

Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need. 

#LI-TS1

The ideal candidate is local to and interested in working from any of our offices (Silver Spring, NYC, SF, Miami, Denver) local to them 1-2x per week.

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Core enables every engineering team at Rocket Money to move fast by keeping our foundational systems reliable and easy to build on. We own and evolve the platforms and services that sit at the center of the product and company operations, including:

• Authentication (registration, login, account access, and user lifecycle workflows)
• Data privacy and trust systems (privacy requests, user deletions, and secure handling of sensitive data)
• AI enablement (shared AI infrastructure and tools that other teams leverage to build great product experiences)
• Internal tooling (admin tooling, operational systems, and data integrations that keep our operations & engineering teams effective)

We care deeply about correctness, resiliency, and making the “paved path” the easiest path. If you like building high-leverage systems that others depend on, this team is for you.

IN THIS ROLE, YOU'LL:

• Build and operate Core services and platforms that power foundational systems like authentication, data privacy workflows, AI enablement, and internal tooling.
• Own projects end-to-end: problem definition, technical design, implementation, rollout, and ongoing reliability.
• Partner closely with product engineers, data teams, and operations partners to create systems that are safe, scalable, and pleasant to use.
• Improve reliability and observability across critical workflows by instrumenting services, debugging production issues, and raising engineering standards.
• Help define and strengthen the platform patterns other teams use (APIs, libraries, service templates, authentication patterns).
• Write clear design docs and RFCs, participate in code reviews, and contribute to a culture of thoughtful feedback and continuous improvement.

ABOUT YOU 🦄

• You have 7+ years of professional experience working with some combination of Node.js/TypeScript, React (or similar framework), and Postgres (or similar relational database). Experience with GraphQL is a plus.
• You're not just interested in what you're building, but also why you're building it. You want to see the bigger picture of how the software you‘re building is benefitting our users.
• You are highly autonomous. You can take an ambiguous problem, align with stakeholders, and drive it to a reliable production outcome.
• You are an early adopter of AI-assisted engineering workflows and consider these tools a core part of how you ship. You use tools like Claude Code, Cursor (or similar) to accelerate exploration, implementation, debugging, and iteration while maintaining strong engineering judgment.
• You’re effective in a large organization, building trust across teams, untangling ownership and dependencies, and maintaining momentum from ambiguity through execution.
• You understand how observability impacts reliability and enjoy digging into the details to solve performance, data accuracy, and user experience issues.
• You have a collaborator’s mindset and dig deep to understand nuanced and multi-faceted problems and tenaciously break them down into tractable pieces. You love giving and receiving feedback, and considering new and novel ideas.

BONUS POINTS FOR ✨

• Auth & identity: Auth0, OAuth, SSO, session management
• Privacy & sensitive data: access requests, deletion workflows, least-privilege patterns
• AI enablement / LLMOps: model gateways, prompt tooling, provider integrations

WE OFFER 💫

• Health, Dental & Vision Plans
• Life Insurance
• Long/Short Term Disability
• Competitive Pay
• 401k Matching
• Team Member Stock Purchasing Program (TMSPP)
• Learning & Development Opportunities
• Tuition Reimbursement
• Unlimited PTO
• Daily Lunch, Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional Information: Salary range of $150,000 - $185,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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

The Role

We’re looking for an Applied AI Engineer to help build the next generation of agentic systems. This role combines deep software engineering skills with an experimental mindset around how AI can be practically applied to solve real user problems.

You’ll collaborate across product, research, and engineering to design agents that reason, interact with environments and evolve through feedback. Ideal candidates bring curiosity, a love of ambiguous problems, and hands-on experience applying LLMs in production.

What You'll Own

• Build autonomous and semi-autonomous agent workflows that interact with browsers, codebases, and APIs to complete complex content operations.
• Evaluate model behavior in live environments and pioneer approaches for applying reinforcement learning to end-to-end agent systems.
• Design modular frameworks for tools, memory, and evaluators to enable continuous learning and improvement of agents.
• Develop data pipelines to collect, transform, and annotate real-world usage data for SFT and RL training.
• Design and build proprietary agent libraries, prompting strategies and benchmarking frameworks.
• Partner with customers and internal stakeholders to understand edge cases and align AI behaviors with user expectations.

What We're Looking For

• 4+ years of software engineering experience, with at least a year working directly on AI/ML-powered applications. 
• Strong fluency in AI tooling (e.g. OpenAI APIs, Anthropic APIs). 
• Practical understanding of LLMs, prompt engineering and agentic architectures.
• Experience building production systems that integrate external environments - code execution, browser automation or API orchestration.
• High degree of ownership and comfort in experimental, fast-moving environments.

Nice to Have

• Familiarity with benchmarks like SWE-bench or evaluation strategies for tool-using agents.
• Exposure to customer-facing roles or user research for AI product development.
• Background in reinforcement learning or data-centric AI approaches.

Compensation

The salary range for this position is $130,000 – $220,000 annually. Final compensation will be determined based on factors such as experience, skills, and qualifications. In addition to base salary, this role may be eligible for performance-based bonuses and equity awards. Gradial offers a comprehensive benefits package, including medical, dental & vision insurance, 401K retirement plan, paid time off, paid sick leave and other employee wellness programs. 

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end.

Main Responsibilities

• Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform.
• Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows.
• Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role.
• Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow.
• Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup.
• Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices.
• Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
• Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
• Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
• As part of our team, you will have the opportunity to work on all aspects of complex National Security problems.
• Annual travel up to 25%.

Preferred Qualifications

• B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
• 3+ years of customer-facing experience in the design and implementation of AI/ML solutions.
• Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow).
• Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI).
• Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
• Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
• Ability to work in a fast-paced environment and balance priorities across multiple projects at once.
• Experience reviewing and drafting responses to federal Requests for Comment (RFCs), Requests for Information (RFIs), Requests for Proposals (RFPs), etc. is preferred
• Experience working across the Civilian, DOD and NATSEC agencies, inclusive of experience in Federal Law Enforcement, Healthcare, Financial/Regulatory and Military operations and logistics
• Candidates must have an active TS (Top Secret) Clearance

Compensation range $170K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Locations

#LI-CG1

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As a member of the Product and Engineering organization, you will join a team of builders, innovators, and problem solvers focused on amplifying the impact of AI across PitchBook. We value curiosity, pragmatic experimentation, and a relentless focus on improving how teams work.

As a Senior Software Development Engineer, AI Enablement, you will serve as a senior individual contributor and force multiplier for engineering, product, research, and business teams by designing and building AI-powered developer productivity and general productivity tools. Your mission is to reduce friction, accelerate delivery, and embed AI as a natural extension of everyday work across the company.

Rather than focusing on core infrastructure ownership, this role emphasizes internal platforms, developer tools, workflows, and enablement patterns that help teams build, ship, and operate faster using AI. You will work closely with engineers, product managers, and non-technical partners to translate ambiguous, real-world pain points into scalable, high-impact solutions.

In this senior role, you are expected to operate with a high degree of autonomy, lead complex initiatives end-to-end, and raise the technical bar through strong design, implementation, and mentorship. Your work will directly influence how PitchBook teams use Generative AI, LLMs, and automation to create value—helping the company move faster, innovate more effectively, and fully realize the benefits of its AI investments.

Primary Job Responsibilities:

• Act as a senior technical force multiplier by building AI-powered tools, workflows, and “golden paths” that significantly accelerate delivery and reduce cognitive and operational overhead
• Design, implement, and iterate on internal AI-enabled productivity tools (e.g., coding assistants, research accelerators, workflow automation, decision-support tools) used by teams across the company
• Lead the technical design and execution of complex AI enablement initiatives, from problem discovery through production adoption
• Partner deeply with engineering, product, and business teams to identify high-impact opportunities where AI can meaningfully improve speed, quality, or scale
• Build reusable software components, libraries, and reference implementations that make AI easy, safe, and consistent to adopt
• Set and uphold high standards for code quality, system design, reliability, and maintainability
• Collaborate in an Agile environment with engineers, product managers, and cross-functional stakeholders
• Provide technical leadership through code reviews, design reviews, mentorship, and hands-on collaboration
• Own projects end-to-end with minimal oversight, making sound technical and product trade-offs
• Continuously evaluate emerging AI tools, frameworks, and best practices and translate them into practical internal capabilities
• Champion responsible, secure, and scalable AI usage across the organization
• Support PitchBook’s culture and values by modeling curiosity, collaboration, ownership, and continuous improvement
• Contribute to the evolution of PitchBook’s AI capabilities and enablement strategy
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Degree in Computer Science, Software Engineering, or a related field
• 5+ years of professional software development experience with demonstrated ownership of complex systems
• Strong proficiency in Python (experience with JavaScript/TypeScript or Java is a plus)
• Hands-on experience building developer tools, internal platforms, or productivity-focused software used by other engineers
• Practical experience working with Generative AI and LLMs (e.g., OpenAI APIs, LangChain, or similar frameworks)
• Experience integrating AI into real-world, production workflows rather than purely experimental prototypes
• Solid understanding of prompt engineering, evaluation techniques, and responsible AI patterns
• Experience designing APIs, services, or libraries consumed by multiple teams
• Comfort working with SQL and/or NoSQL databases
• Strong understanding of Git, CI/CD workflows, testing strategies, and modern development practices
• Proven ability to operate in ambiguous problem spaces and independently identify high-leverage opportunities
• Strong communication and stakeholder collaboration skills with the ability to explain complex technical concepts clearly
• Track record of mentoring other engineers and raising the technical bar on a team
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $160,000-$200,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-KL1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Staff Software Development Engineer, AI Enablement, you will operate as a technical leader and force multiplier across Product, Engineering, Research, and Business teams. Your role is to define, build, and scale AI-powered productivity capabilities that fundamentally change how PitchBook teams work, ship, and innovate. 

This is a high-impact, high-autonomy role focused on software systems, internal platforms, and developer productivity tools, rather than core infrastructure ownership. You will identify the highest-leverage opportunities for AI enablement, set technical direction, and deliver reusable solutions that accelerate delivery, improve quality, and reduce friction across the organization. 

You will partner closely with engineering leaders, product leaders, and executive stakeholders to ensure AI is embedded into workflows in a safe, scalable, and repeatable way. Your work will directly influence PitchBook’s ability to move faster than competitors, fully realize the value of AI investments, and attract and retain top technical talent. 

Primary Job Responsibilities:

• Act as a technical force multiplier at the organizational level, designing AI-powered tools and workflows that unlock step-change productivity gains 
• Define and own the technical vision and roadmap for internal AI enablement and developer productivity capabilities 
• Architect and build scalable internal platforms, libraries, and “golden paths” that make AI easy, safe, and effective to adopt 
• Identify systemic bottlenecks in development, research, and knowledge workflows and translate them into high-impact AI solutions 
• Lead complex, ambiguous initiatives end-to-end, from problem framing and experimentation through production adoption 
• Partner with senior engineers, managers, product leaders, and non-technical stakeholders to align solutions with business priorities 
• Establish best practices, patterns, and standards for AI usage across teams, including quality, safety, and evaluation 
• Provide technical leadership through design reviews, mentorship, and hands-on collaboration across multiple teams 
• Evaluate emerging AI technologies and translate them into practical, production-ready capabilities 
• Champion responsible AI usage, scalability, and long-term maintainability 
• Model PitchBook’s values by fostering a culture of curiosity, collaboration, and continuous improvement 
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Degree in Computer Science, Software Engineering, or related field (or equivalent experience) 
• 8+ years of professional software development experience, with demonstrated impact at scale 
• Proven experience leading cross-team technical initiatives or internal platforms 
• Deep proficiency in Python; experience with additional languages (e.g., JavaScript/TypeScript, Java) is a plus 
• Strong hands-on experience building AI-enabled products or productivity tools using LLMs and GenAI frameworks 
• Experience designing APIs, shared services, or developer platforms used by multiple teams 
• Strong understanding of prompt engineering, evaluation strategies, and responsible AI patterns 
• Experience translating ambiguous business problems into scalable technical solutions 
• Solid grounding in modern development practices (Git, CI/CD, testing, observability) 
• Excellent communication skills with the ability to influence without authority 
• Track record of mentoring senior engineers and raising the technical bar across teams 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $185,000 - $240,000
• Target annual bonus percentage: 15%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-KL1

#LI-Onsite

The ideal candidate is local to and interested in working from any of our offices (Silver Spring, NYC, SF, Miami, Denver) local to them 1-2x per week.

ABOUT ROCKET MONEY 🔮

Rocket Money's mission is to empower people to live their best financial lives. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Machine Learning Engineers at Rocket Money further our mission by building products that deepen customer relationships with our many financial products. Our work ranges from transaction enrichment to personalization to cross-functional tools that support various AI product initiatives. We work closely with product teams to develop features that help customers understand, track, and improve their personal finances. We have a strong preference for team players that are comfortable collaborating across teams, know how to support strategy with ML and AI powered user experiences, can deliver scalable and high quality user experiences, and understand the effects of their products on end users. At the Staff level, Machine Learning Engineers are expected to build broad expertise into our products and the ML solutions that power them as well as drive technical progress for the team.

ABOUT THE ROLE 🤹

As a Staff Machine Learning Engineer at Rocket Money, you will be at the forefront of our ML and AI product development, bringing your expertise to design, implement, and maintain sophisticated ML systems that drive our product experiences. You will:

• Lead the architecture and development of complex AI and ML powered features across Rocket Money's product suite, proactively identifying technical challenges before they become issues.
• Design, implement, and maintain robust evaluation frameworks. You ensure that ML/AI systems can be constantly improved and create frameworks so that others can do the same.
• Develop novel new product experiences that you are uniquely positioned to enable for users. Help Rocket Money capitalize on it’s unique dataset and scale. Guide others to help generate impact through effective technical leadership and partnership with product.
• Own end to end development and implementation of ML and AI product features in collaboration with cross-functional product development teams. Rigorous technical critique and oversight coupled with effective communication of business impact are musts.
• Provide technical mentorship, fostering an environment where everyone can contribute to high-impact work. You will raise the level of everyone around you.

Potential Projects:

• Develop comprehensive evaluation and ML Ops frameworks that enable systematic assessment of model performance, supporting rapid iteration and improvement of AI/ML product features.
• Scale transaction metadata generation systems to billions of financial transactions in a consumer facing app. Implement AI assisted transaction management and personalization features such as personalized categories, income and rent detection, and subscription identification.
• Implement effective user feedback mechanisms that enable measurement of ML feature product quality and constant improvement.
• Architect user facing predictive features that depend on fast moving and large scale user transaction data.

ABOUT YOU 🦄

• 8+ years of professional experience in machine learning engineering or data science roles, with a proven track record of designing and implementing ML systems at consumer tech scale and speed.
• Extensive hands-on experience integrating ML and AI methods into production workflows, including creating evaluation tooling and effective user feedback mechanisms to support rapid product development cycles and systematic model evaluation.
• Experience with prompt engineering and management, creating robust systems for testing and optimizing LLM-based applications.
• Expert-level proficiency in Python, SQL, and at least a handful of common ML frameworks. Working Typescript knowledge is a plus. You understand ML methods at a fundamental level - deep experience in NLP techniques is a plus.
• You are a master at taking ambiguous problems, creating clarity, and breaking down work into manageable chunks for implementation. You’ve owned the development, launch, and maintenance for several scaled ML/AI powered product experiences.
• You understand basic software engineering and computer science fundamentals and have applied them at consumer grade scale to build ML powered products in production environments.
• You are a technical leader who can identify both emergent technical opportunities and gaps relative to best practice. Your strong communication skills enable your team to capitalize on these opportunities and generate impact.
• You care about products and user experiences, not publications. You are a practitioner first and thrive at the (messy) intersection of the real world and cutting edge approaches.

WE OFFER 💫

• Health, Dental & Vision Plans
• Competitive Pay
• 401k Matching
• Unlimited PTO
• Lunch daily (in-office only)
• Snacks & Coffee (in-office only)
• Commuter benefits (in-office only)

Additional information: Salary range of $210,000 - $260,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Rocket Money is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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