AI Engineer (LLM)

Location: Remote, United States; listed location: Chicago (Green St), IL

Company

hirify.global provides a cloud platform for the insurance economy, serving insurers, repairers, automakers, and parts suppliers with AI-powered claims and repair technology.

What you will do

• Ship LLM-powered features and agentic workflows in Python and TypeScript from product scoping through production, defining and tracking outcome metrics.
• Design evals, guardrails, feedback loops, token budgets, and latency budgets for trustworthy AI features.
• Build and operate event-driven services with deterministic workflows, retries, idempotency, checkpointed model outputs, and shared on-call ownership.
• Maintain NLP pipelines combining semantic search, classical NLP, structured output, tool calling, embeddings, and LLMs for unstructured claims data.
• Trace model calls and agent steps for auditability, citations, alerts, and production debugging.
• Design privacy and security controls including tenant isolation, least-privilege agent access, and rules governing data sent to model providers.

Requirements

• 3+ years of professional software engineering experience, including at least one LLM-powered feature shipped and operated in production.
• Typed, tested, asynchronous Python and TypeScript code, with deep expertise in at least one of them.
• Experience designing LLM output evals and shipping guardrails.
• Production use of Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools, including constraining context and verifying generated output for correctness, security, and design.
• Experience building pipelines that combine LLMs, semantic search, and classical NLP, including structured output, tool calling, embedding-based retrieval, and a case where a classical technique outperformed an LLM.
• Experience with message- or event-driven architectures, long-running workflows, retries, idempotent handlers, event-sourced state, and running an LLM or agent step within such a workflow.
• Experience modeling and developing across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including partition-key, consistency, and tenant-isolation decisions.
• Backend services operated on Azure or AWS, plus exposure to Temporal or the Durable Task Scheduler.
• Technical design documents written to obtain team feedback and buy-in before implementation, followed by team adoption.
• Clear technical and non-technical communication and the ability to give and receive code review.

Nice to have

• React and TypeScript experience for full-stack features, especially chat, streaming, and citation-heavy AI experiences.
• CI/CD and infrastructure as code with Terraform or Bicep.
• Agent frameworks such as LangGraph or Microsoft Agent Framework, and agent tool integrations through MCP, A2A, command-line tools, or microservices.
• LLM observability and evaluation tools such as LangSmith, Arize, or Braintrust, plus OpenTelemetry tracing.
• A/B testing for AI features or what-if simulations replaying historical claims before release.
• Insurance, claims, or automotive repair experience.

Culture & Benefits

• Remote workplace with full-time employment.
• Shared on-call rotation for owned services.
• Benefits include 401(k) matching, paid time off, health insurance, an annual incentive plan performance bonus, adoption assistance, tuition reimbursement, wellness programs, stock purchase plan options, and employee resource groups.
• Values emphasize integrity, customer focus, innovation, inclusion and diversity, tenacity, and connection.
• Video interviews are required and transcribed; generative AI or automated assistance is not permitted during interviews unless explicitly authorized for a specific exercise.

Hiring process

• Complete a required video interview; transcripts are retained and may be reviewed by CCC and its recruiters.
• Do not use generative AI or automated assistance during interviews unless the interview team explicitly permits it for a specific exercise.