LLM AI Engineer: End-to-End, Secure Production

EvolutionIQ; Chicago (IL); Hybrid; USD 170,000 - 195,000; Full time

Benefits offered by this job

401K Match

Paid time off

Annual Incentive Plan PerformanceBonus

Adoption Assistance

Tuition Reimbursement

Wellness Programs

Stock Purchase Plan options

Employee Resource Groups

Job summary

CCC Intelligent Solutions Inc. in Chicago seeks an AI Engineer to build and ship LLM-powered features and agentic workflows for customers. You will design, implement, and operate end-to-end solutions with privacy and security as baselines, delivering production-ready components and measurable outcomes.

You'll own the NLP pipelines, data modeling across databases, and durable, event-driven services. Expect collaboration with product managers and data scientists, plus on-call responsibilities and

Qualifications

• 3+ years of professional software engineering experience, including at least one LLM-powered feature you shipped and then operated in production.
• Python and TypeScript: typed, tested, async code in both, and real depth in one.
• Evals you have designed for LLM output, plus guardrails you have shipped.
• A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work.
• Pipelines that blend LLMs with semantic search and classical NLP: structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM.
• Services built on message- or event-driven architectures, including long-running workflows with retries, idempotent handlers, and event-sourced state, plus an LLM or agent step you ran inside one.
• Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made.
• Backend services built and operated on Azure or AWS, and exposure to a durable workflow engine such as Temporal or the Durable Task Scheduler.
• Technical design documents you have written to get feedback and buy-in from a team before building, and that the team then built to.
• Clear writing and discussion for technical and non-technical audiences, and code review you can give as well as take.

Responsibilities

• Ship LLM-powered features and agentic workflows in Python and TypeScript, from a problem scoped with product managers and data scientists through production traffic.
• Write the evals, guardrails, and feedback loops that make your features trustworthy, and hold them to explicit token and latency budgets.
• Use agentic coding tools every day, and own the review of what they produce: catch the correctness, security, and design problems in generated code before you open the pull request.
• Maintain and extend the NLP pipelines that turn unstructured claim data into structured data customers can act on, blending semantic search, classical NLP, and LLMs.
• Build and operate durable, event-driven services in which agents run as steps inside deterministic workflows, with checkpointed model outputs so a retry does not re-invoke a completed LLM step.
• Trace every model call and agent step so a recommendation can be reconstructed and audited, with citations back to the source documents, and wire that tracing into your alerts.
• Model and query claims data across relational, document, and graph stores.
• Design privacy and security in from the start: tenant isolation, least-privilege access for agents and their tools, and a clear rule for what data may reach a model provider.
• Write a technical design document before any significant change, and use it to get feedback and buy-in from the team before you build.
• Take part in a shared on-call rotation for the services you build.

Skills

Python

TypeScript

LLM features

NLP pipelines

Security design

Tools

Azure

AWS

PostgreSQL

MongoDB

Neo4j

Temporal

OpenTelemetry

LangGraph

Job description

CCC Intelligent Solutions Inc. in Chicago seeks an AI Engineer to build and ship LLM-powered features and agentic workflows for customers. You will design, implement, and operate end-to-end solutions with privacy and security as baselines, delivering production-ready components and measurable outcomes.

You'll own the NLP pipelines, data modeling across databases, and durable, event-driven services. Expect collaboration with product managers and data scientists, plus on-call responsibilities and