AI Agent Engineer
About The Position
We're looking for an AI Agent Engineer to design, build, and scale the agent platform that powers our AI capabilities. You'll work at the intersection of large language models, complex business workflows, and real production systems—building the core infrastructure that turns manual, expertise-heavy processes into reliable, autonomous capabilities. This is a high-ownership role. You'll ship the agents that parse dense policy documents, automate email workflows, build knowledge representations of client risk profiles, and handle real client work end-to-end. You'll architect the systems that make these agents trustworthy, observable, and extensible—so they can be deployed across workflows by the rest of the team. This isn't a role where you're configuring tools or wiring up APIs. You'll solve hard infrastructure problems: task decomposition, tool use, memory, error recovery, human-in-the-loop patterns, and evaluation frameworks. You'll build the foundation that our Applied AI Engineers deploy on top of.
Requirements
- 3+ years building software in production environments, with hands-on experience developing LLM-powered applications.
- You've built agents or agentic systems. You understand tool use, planning, evaluation, and the challenges of making AI reliable.
- Strong fundamentals in software engineering: you write clean code, design sensible systems, and ship consistently.
- You think from first principles. You can navigate ambiguity, make tradeoff decisions, and figure out what to build when there's no playbook.
- You want ownership. You're excited by autonomy and accountability, not layers of process.
Nice To Haves
- Experience with document processing, embeddings, RAG, or knowledge graphs is a strong plus.
- Comfortable across the stack. Experience with our core technologies is a plus: Node.js, GraphQL, Postgres, React/Next.js.
Responsibilities
- Build the Agent Platform. Design and implement the core agent infrastructure that powers automation across the business. Own the architecture—task orchestration, tool use, memory systems, and error handling patterns. Build systems that are reliable enough to handle real client work.
- Engineer Reliable AI Systems. Architect agentic systems that work at scale: multi-step reasoning, structured extraction from unstructured data, and multi-agent coordination. Build evaluation frameworks to measure agent quality, catch regressions, and iterate with confidence.
- Build for Extensibility. Design the platform so others can build on top of it. Create the abstractions, APIs, and patterns that let Applied AI Engineers ship workflow solutions quickly without reinventing the plumbing. Your infrastructure should multiply the team's output.
Benefits
- Competitive compensation that may include equity
- Flexible paid time off
- Comprehensive benefit plans for medical, dental, vision, life, and disability
- Flexible Spending Accounts (FSAs): Health Care FSA and Dependent Care FSA
- Commuter Savings Account
- Human Interest: 401(k) provider
- Time Off: Sick Leave, Family and Medical Leave, Flexible Time Off
- Paid Holidays: Observance of all major national holidays
- A curated in-office employee experience, designed to foster community, team connections, and innovation, that also includes catered lunches in the office on Fridays for in-office workers
- Collaborative, transparent, and fun culture
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
