Sr. AI Developer

Goodwin•Washington, DC

9d•$134,300 - $236,500

About The Position

Join Goodwin’s Global Operations Team, and make a real impact on a global scale. At Goodwin, we work with some of the world’s most successful and innovative investors, entrepreneurs and disruptors in the life sciences, private equity, real estate, technology and financial industries, and where they converge. As part of the Global Operations Team – all business professionals at the firm – you’ll collaborate with colleagues from varied backgrounds and experiences, fostering an environment where cross-functional learning, networking, and collaboration are at the core of what we do. Here, we’re not just supporting a law firm; we’re partnering with attorneys and clients to deliver cutting-edge solutions in high-stakes litigation and dispute resolution, world-class regulatory compliance and advisory services, and complex transactions. Our commitment to integrity, ingenuity, agility, and ambition drives us, and we’re proud to have been recognised as the “Best Business Team” by The American Lawyer. This is your opportunity to grow professionally in a dynamic, global environment, surrounded by forward-thinking peers. We’re seeking a product-minded Senior AI Engineer to build and scale production-grade AI agents and agentic systems across Goodwin. This hands-on, builder-first role owns problems end to end, from workflow discovery and system design through deployment, adoption, and continuous optimization, shipping full-stack solutions that are fast, reliable, and deliver measurable business impact. Above all, this is a role for a strong software engineer: we expect deep engineering fundamentals, sound system design, and a track record of shipping reliable production-grade software. This is a senior individual-contributor role for someone with the agency to take an ambiguous problem and drive it to a shipped, reliable system with minimal oversight. The position reports to the Director of Engineering and works closely with cross-functional teams, including other developers, architects, and business stakeholders.

Requirements

Minimum 3–5 years building and shipping software to production
Bachelor’s degree or equivalent practical experience.
Strong software engineering fundamentals, including data structures, system design, and testing, with full-stack coding ability in languages such as Python, C#, and modern TypeScript/React; consistently produces maintainable code, tests, and high-quality PRs.
Experience running software in production, from CI/CD and observability to incident response, and applying that to deploying and operating LLM/agent solutions.
Comfort with ambiguity, able to translate loosely defined problems into clear specs, milestones, and working systems.
High ownership and a bias to action, focused on shipping, measuring impact, and iterating quickly over polishing demos.
Strong communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
High agency and a strong service orientation, able to run with loosely defined problems independently, manage competing priorities, and build effective working relationships with attorneys, staff, and technical partners across the firm.

Nice To Haves

Experience with Azure AI Foundry or adjacent Azure AI services is a plus, but comparable cloud/AI platform experience is welcome.
Experience with RAG over internal documents (chunking, indexing, retrieval tuning) and evaluation of retrieval quality.
Experience working autonomously in a culture that is builder minded and focused on quick delivery
Experience integrating agents with internal systems via APIs, queues, and workflow tools, and working within a structured SDLC in an enterprise environment.
Familiarity with security-focused or regulated environments (PII handling, least-privilege access, auditability), and setting up automated evals (golden sets, regression tests) for prompts and agents.

Responsibilities

Own projects from zero to one as an engineer, covering problem framing, system design, implementation, deployment, monitoring, and iteration, with AI and agentic systems as the current focus.
Embed with business/legal teams to map workflows, identify high-leverage bottlenecks, and streamline them using AI backed solutions
Design agent architectures spanning tools and functions, memory and state, retrieval, and guardrails, using common LLM orchestration frameworks (such as LangChain/LangGraph, Microsoft Agent Framework, or LlamaIndex), and write prompts that are testable and versioned.
Build full-stack features, primarily in C#/.NET, Python, and TypeScript/React, writing well-structured services, clean APIs, and tested code that make agents usable, safe, and fast for internal users.
Ship on Azure, today largely via Microsoft Azure AI Foundry and adjacent Azure AI services, owning model selection, evaluation, deployment pipelines, and production operations.
Instrument quality by defining success metrics, building evals and test suites, reducing hallucinations and failure modes, and driving reliability over time.
Perform comprehensive testing, debugging, and troubleshooting of AI agents to ensure quality and minimize defects.
Partner with security and compliance to ensure responsible data handling, least-privilege access, and auditability.
Document agent designs, architectures, and operational guidelines to ensure maintainability and knowledge transfer.
Drive delivery with a disciplined engineering approach, applying a structured SDLC across design, development, testing, and deployment, and raise the bar for code quality, pragmatic architecture, and reliable operations.