Ai Engineer Jobs

About The Position

Requirements

• At least 3 years of professional software engineering experience, including having shipped and operated at least one LLM-powered feature in production.
• Typed, tested, asynchronous Python and TypeScript code, with substantial depth in at least one of the languages.
• Experience designing evaluations for LLM output and shipping guardrails.
• Daily production use of an agentic coding tool such as Claude Code, Cursor, or GitHub Copilot, with the ability to explain how you constrain its context and verify its output.
• Experience building pipelines that combine LLMs, semantic search, and classical NLP, including structured output, tool calling, embedding-based retrieval, and an example where a classical technique outperformed an LLM.
• Experience with message- or event-driven architectures, including long-running workflows, retries, idempotent handlers, event-sourced state, and an LLM or agent step within a workflow.
• Experience modeling and developing across relational, document, and graph databases, such as PostgreSQL, MongoDB, and Neo4j, including database selection, partition-key, consistency, and tenant-isolation decisions.
• Experience building and operating backend services on Azure or AWS, and exposure to a durable workflow engine such as Temporal or Durable Task Scheduler.
• Experience writing technical design documents to obtain team feedback and buy-in before implementation.
• Clear written and verbal communication with technical and non-technical audiences, and the ability to give and receive code review.

Nice To Haves

• React and TypeScript experience to deliver full-stack features.
• Experience with chat, streaming, and citation-heavy AI experiences.
• Experience with CI/CD pipelines and infrastructure as code such as Terraform or Bicep.
• Experience with agent frameworks such as LangGraph and Microsoft Agent Framework, and agent tool-access approaches including MCP, A2A, command-line tools, and microservices.
• Experience with LLM observability and evaluation tools such as LangSmith, Arize, or Braintrust, and OpenTelemetry-based tracing.
• Experience designing A/B tests for AI features or what-if simulations that replay historical claims before a change ships.
• Exposure to insurance, claims, or automotive repair domains.

Responsibilities

• Ship LLM-powered features and agentic workflows in Python and TypeScript, from product and data-science scoping through production, and help define success metrics.
• Write evaluations, guardrails, and feedback loops for trustworthy features; manage explicit token and latency budgets.
• Use agentic coding tools and review generated code for correctness, security, and design issues before submitting pull requests.
• Maintain and extend NLP pipelines that structure unstructured claim data using semantic search, classical NLP, and LLMs.
• Build and operate durable, event-driven services with agents as steps in deterministic workflows and checkpointed model outputs to avoid repeating completed LLM steps on retries.
• Trace model calls and agent steps for reconstruction and auditability, including citations to source documents, and connect tracing to alerts.
• Model and query claims data across relational, document, and graph data stores.
• Design privacy and security controls, including tenant isolation, least-privilege access for agents and tools, and rules governing data sent to model providers.
• Write technical design documents before significant changes and obtain team feedback and buy-in before implementation.
• Participate in a shared on-call rotation for services built by the team.

Benefits

• 401K Match
• Paid time off
• Annual Incentive Plan
• Performance Bonus
• Comprehensive health insurance
• Adoption Assistance
• Tuition Reimbursement
• Wellness Programs
• Stock Purchase Plan options
• Employee Resource Groups