AI Engineer

• Define and maintain enterprise architecture standards, reference patterns, and governance guardrails for AI-enabled solutions moving from pilot to production.
• Establish decision models for build, buy, or integrate choices; model and vendor selection; data access; security; and responsible AI adoption.
• Design scalable architecture patterns for AI-enabled workflows and agentic processes across data, APIs, identity, security, and cloud platforms.
• Test new AI models, LLMs, agent frameworks, and tools to inform enterprise adoption.
• Design proof-of-concepts, define success criteria, and guide solutions from pilot to production.
• Lead architecture reviews and communicate trade-offs, risks, and growth to partners.
• Partner with teams to translate needs into governed, implementation-ready solutions.
• Ensure teams through demos, workshops, and reusable templates to support safe AI adoption.

Principal Architect – Enterprise AI

• As a Senior AI Engineer within Bristol Myers Squibb's AI Venture Studio team, you will be a hands-on individual contributor responsible for building secure cloud-hosted applications.
• Design APIs, services, infrastructure patterns, deployment pipelines, and semantic-layer evolution patterns for agent context engineering.
• Collaborate with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
• Create and maintain CI/CD pipelines, environment configuration, automated tests, and release processes for cloud AI applications.
• Partner with AI Engineers, Data Engineers, Data Scientists, and product teams to solve complex delivery challenges.
• Continuously refine delivery priorities and deliver MVP transition activities by maturing AI capabilities.

Senior AI Engineer

• Define and evolve the standards, architecture patterns, and tooling choices that govern how engineers use AI across the codebase — including where to invest in codebase readiness (instrumentation, specification, evaluation) versus targeted rewrites.
• Own execution of the multi-milestone plan (readiness → validated → governed) applied to corgi and secondary repos, in partnership with squad leads — without being their manager.
• Decide what AI tooling, agent infrastructure, and evaluation pipelines the org needs, and build or oversee the build of the ones that don't exist yet.
• Set the policy and technical controls for where human-in-the-loop review is required versus where autonomous agent action (PR review, deployment) is safe — resolving the tension between adoption speed and security/quality risk.
• Write the guidance engineers actually use — AGENTS.md/CLAUDE.md conventions, review norms for AI-generated code, eval standards — and make sure it's adopted, not just published.

AI Architect

• Improve operational efficiency, resilience, and process quality by establishing scalable AI automation architecture standards and governance guardrails
• Accelerate transformation delivery and reduce rework through clear design frameworks, decision models, and reusable automation patterns
• Enhance employee and customer experience by reducing manual work, process fragmentation, and automation risk
• Embed AI-first architectural practices that improve automation scale, decision quality, and measurable business outcomes
• Lead evaluation of AI automation, agentic workflow, and transformation initiatives across the organization
• Define architectural decision frameworks and long-term platform strategy for n8n, Boomi, APIs, event-driven orchestration, and AI services to reduce duplication and increase reuse
• Establish governance guardrails for AI-enabled workflows, agents, prompts, models, data flows, and human-in-the-loop controls to ensure scalability, reliability, auditability, and responsible use
• Anticipate growth, compliance, security, and operational risks across automation platforms and transformation programs before they materialize
• Influence cross-functional roadmaps with AI Automation Engineers, BSAs, and business leaders based on architectural trade-offs, platform fit, and measurable outcomes
• Translate enterprise capability needs into clear, implementable technical designs that accelerate AI automation delivery
• Create architectural blueprints for intelligent workflows, agentic process patterns, and cross-system orchestration that reduce ambiguity and minimize rework
• Design secure, scalable, and resilient automation patterns across SaaS systems, internal platforms, APIs, data ecosystems, and AI/ML services
• Drive API-first, event-driven, and human-in-the-loop architecture standards that improve interoperability, control, and long-term maintainability
• Lead architecture reviews and represent AI automation and transformation strategy in executive and cross-functional forums

Principal Enterprise AI Architect

• Partner with internal and external stakeholders to re-envision and scale Core Engineering technologies, including the design and build of a suite of AI Agents
• Drive technical excellence and governance of AI Agents as use-cases are identified across Snap Engineering
• Collaborate across teams to understand product requirements, evaluate architectural trade-offs, and deliver solutions needed to build innovative products and services
• Champion best practices in availability, scalability, operational excellence, and cost management
• Serve as a technical mentor to senior engineers and a thought partner to engineering leaders
• Contribute to the technical roadmap for AI Agents and Core SWE infrastructure, ensuring alignment with organizational goals
• Partner closely with Product, Finance, Sales, and Engineering teams distributed across multiple offices
• Influence key architectural and implementation decisions for scalable, reliable, and cost-effective engineering solutions
• Iterate quickly without compromising quality and continuously raise the bar on operational excellence
• Adapt technical plans nimbly in response to evolving customer and business needs

Staff Software Engineer, DevProd AI

• Design, build, test, and deploy AI legal workflows and skills across firm-approved AI tools, supporting use cases such as contract review, due diligence, drafting, research, and summarization
• Partner directly with attorneys and knowledge management professionals to identify high-value use cases, map workflows, and translate practice needs into structured AI solutions
• Develop and maintain retrieval pipelines, document templates, and reusable workflow components with clear, attorney-ready documentation
• Build and execute evaluation frameworks to measure workflow quality, accuracy, and reliability; monitor performance and iterate based on feedback and outcomes
• Serve as a go-to resource for enablement and change management for developed workflows, partnering with the AI Adoption team to drive usage, deliver training sessions and workshops, 1:1 coaching, and develop practical playbooks and materials that support sustained adoption
• Develop and scale best-practice standards, use-case libraries, and playbooks that empower attorneys to responsibly and independently leverage AI tools while maintaining quality and risk controls
• Embed human-review checkpoints and audit mechanisms aligned with Firm governance, confidentiality, and professional responsibility requirements
• Collaborate closely with cross-functional stakeholders including the AI Product team, AI Adoption team, Knowledge & Innovation team, IT, Innovation Practice Group, and Professional Development to ensure aligned delivery and support
• Track adoption, usage, and impact metrics for deployed workflows and recommend refinements or expansion opportunities
• Manage ongoing maintenance of production workflows, including updates to prompts, retrieval sources, and guardrails in response to model and platform changes, user feedback, or evolving practice needs
• Represent the AI Products & Adoption team in internal meetings, committees, and practice group sessions

AI Legal Engineer

• Partner with AI Solution Engineers, Architects, and senior technical teammates
• Design, build, and deploy AI-powered solutions for legal customers
• Translate legal workflows and business needs into technical solutions
• Contribute to technical discovery, solution delivery, and prototyping
• Assist with demonstrations, proofs of concept, and early-stage prototypes
• Develop working knowledge of legal terminology and processes
• Design and implement AI-powered solutions for legal workflows
• Collaborate with senior engineers and architects to ensure solutions are scalable
• Evaluate LLM outputs for legal accuracy and relevance

Software Engineer – AI, CoCounsel Forward Deployed Engineering

• Design, develop, and improve scalable infrastructure to support the next generation of AI applications
• Drive improvements in architecture, performance, and reliability
• Collaborate across hardware, software, and research teams
• Stay informed of the latest advancements in AI infrastructure

Senior Applied AI Engineer

• Lead the end-to-end system design, architectural framework, and product integration of Workday’s next generation of intelligent agents.
• Architect how foundational models are safely and reliably integrated into functional, production-grade software.
• Own the design, experimentation, and orchestration of complex agentic workflows, translating cutting-edge AI capabilities into enterprise-grade business value.
• Be a core champion for Responsible and Governed AI—architecting systems with strict guardrails for data privacy, predictability, and explainability.
• Balance high-level system design and hands-on execution, solving critical product constraints like latency, cost, and reliability.

Principal AI Engineer

• Build complete applications, workflow automations, and basic agents within your team's product area using AI coding agents
• Translate customer needs into buildable specifications and ship solutions from requirements through deployment
• Instrument solutions to track usage and outcomes, iterating based on what you learn
• Evaluate AI-generated output against Remitly's standards for security, privacy, reliability, and quality before shipping
• Participate in customer conversations to understand acute problems and identify automation opportunities
• Document your approaches, effective prompts, and patterns for the team

Senior AI Native Software Engineer

AI Native Software Engineer II

• Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
• Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
• Build and operate LLM evaluation and batch-analysis pipelines
• Own traditional ML workflows from data to scheduled production inference
• Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Senior Software Engineer – Applied AI

• As a Senior AI Engineer on the AI Venture Studio team, you will be a hands-on senior individual contributor who leans into artificial intelligence (AI) to design and build impactful solutions to transform patients’ lives.
• This role is accountable for the AI-first engineering of cloud-native applications, agentic AI products, and the knowledge and context infrastructure that powers them.
• You will have access to the latest AI-centric tools and technologies to support activities such as the design of APIs and MCPs, cloud services orchestration, agent runtime deployment, workflow pipeline implementation, and reusable platform pattern development that enables AI Accelerator projects to move fast without giving up reliability, observability, security, or enterprise architectural alignment.
• This role lives inside the AI Accelerator delivery model: six fully agile two-week sprints across a twelve-week cycle to build, test, validate, and prepare minimum viable products (MVPs) for broader organizational adoption and scaling.
• AI Accelerator projects focus on the most challenging and highest-upside pharma-specific problems across R&D, Commercialization, Manufacturing, and Enabling Functions where critical context is buried in unstructured knowledge files, multimodal documents and reports, operational records, and scientific evidence packages.
• Ship in cycles by demonstrating engineering progress and lessons learned every two weeks.
• Focus on AI-first solutioning that prioritizes BMS technology investments (AWS, Claude, LangSmith, etc.) with the best chance of meeting use case and project success metrics.
• Collaborate effectively with other engineers (AI, data, UI/UX, machine learning) and broader agile AI accelerator product teams.
• Demonstrate a curious and inquisitive mindset with broad technical adaptability while staying hands-on with frontier AI technologies, AI coding agents, and the latest agentic engineering capabilities.

• Develop, test, maintain, and enhance software applications and components using modern programming languages such as Python, JavaScript, Java, Go, or similar languages.
• Write clean, secure, maintainable, and efficient code following established software development standards and best practices.
• Collaborate with engineers, product owners, and business users to understand requirements and translate them into technical solutions.
• Troubleshoot, debug, and resolve application issues, escalating risks or complex problems when needed.
• Participate in code reviews and contribute to improvements in code quality, testing, and development practices.
• Support integration of applications with APIs, databases, cloud services, and software tools.
• Use AI-assisted development tools or AI agents to support coding, testing, debugging, and documentation.
• Contribute to continuous improvement of development processes, agile engineering practices, and secure application development.

Software Engineer, AI Engineering – Enablement

• Own stakeholder relationships across Medbridge’s executive team, working with them to find the problems and AI enabled solutions that can expedite, or remove, the current blockers in the business.
• Design, build, and ship AI-powered features across our internal teams, from the user interface to the backend services and AI workflows behind it.
• Build full-stack applications using AI-native engineering workflows and tools such as Claude, Cursor, Codex, and OpenAI and Anthropic APIs.
• Develop APIs, backend services, and automation pipelines that support intelligent product capabilities and production-ready deployments.
• Apply software engineering, DevOps, and MLOps best practices to the testing, deployment, monitoring, evaluation, and optimization of AI solutions.
• Partner closely with our Product and Engineering teams to turn ambiguous goals into scalable internal products.
• Use AI tooling throughout your workflow (coding, code review, testing, and planning) and help push the team’s adoption forward.
• Research emerging AI technologies, LLM implementation patterns, and modern product engineering frameworks, and bring what works back to the team.
• Instrument what you ship and use usage data and evidence to decide what to build, fix, or kill next.

Product Engineer – AI

• This role invites you to step into a foundational engineering space where you will shape the architecture and implementation of distributed systems.
• You will guide the development of our agentic workflow platform, a critical piece of infrastructure designed to bring durability and intelligent automation to our global software network.
• By establishing code designs and engineering standards, your work ensures complex financial workflows run reliably without disruption.
• Beyond technical delivery, you will champion an AI-forward approach to building software quickly and effectively.
• You will serve as a technical guide and mentor, supporting engineers as they navigate highly ambiguous challenges and learn to leverage modern architectural tools.
• Your leadership will directly influence how our global platforms evolve, setting the technical benchmark for engineering teams across the organisation.

Senior Software Engineer, AI Native Product Engineering

• design, develop, and deliver high-quality, secure, and user-centric software solutions
• collaborate cross-functionally to build scalable applications
• lead projects and mentor peers
• develop software focused on simplification, UX, security, and user privacy
• build advanced agentic AI applications that automate complex business processes
• proven expertise in designing and deploying enterprise-grade AI systems
• full-stack experience across Angular, TypeScript, Python, FastAPI, distributed systems, and developer platform engineering
• write clean, functional code and unit tests
• conduct thorough code reviews
• debug and resolve software issues in development and production environments
• coordinate with cross-functional team members to estimate timelines and deliver according to specifications

Software Engineer – AI

• 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 will involve designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of Snorkel’s tooling.
• 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.
• 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%.

Applied AI Engineer – Federal, TS Required

• Identify Practical AI Use Cases
• Work with business leaders and frontline teams to identify AI opportunities with measurable value.
• Translate business pain points into specific AI use cases with users, inputs, outputs, and success metrics.
• Design and Deploy AI-Enabled Solutions
• Design practical AI solutions, including assistants, workflow automation, agentic workflows, document analysis, summarization, classification, knowledge tools, task routing, and decision support.
• Support Agentic AI Workflows
• Help design multi-step AI workflows that can use tools, follow instructions, route tasks, summarize information, update systems, or escalate to humans.
• Drive AI Adoption
• Work directly with users to understand where AI helps and where it adds friction.
• Create training materials, user guides, SOPs, FAQs, demos, office hours, and practical examples.

AI Engineer jobs in Washington

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Principal Architect – Enterprise AI

Senior AI Engineer

AI Architect

Principal Enterprise AI Architect

Staff Software Engineer, DevProd AI

Staff Software Engineer, DevProd AI

AI Legal Engineer

Software Engineer – AI, CoCounsel Forward Deployed Engineering

Senior Applied AI Engineer

Principal AI Engineer

Senior AI Native Software Engineer

AI Native Software Engineer II

Senior Software Engineer – Applied AI

Senior AI Engineer

Software Engineer, AI Engineering – Enablement

Product Engineer – AI

Senior Software Engineer, AI Native Product Engineering

Software Engineer – AI

Applied AI Engineer – Federal, TS Required

AI Solutions Lead