AI Engineer, CCC Auto, Agentic

EvolutionIQ

. Build and ship LLM-powered features and agentic workflows for insurance customers .

Posted 11/5/2026full-timeRemote • Illinois • United StatesMid-LevelSenior💰 $170,000 - $195,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping LLM-powered features and agentic workflows, with a strong focus on Python and TypeScript development. Proficient in data modeling across various database types and experienced in writing technical design documents while ensuring team collaboration and feedback.

Highest-signal resume keywords

LLM-Powered Feature DevelopmentPython and TypeScript ProficiencyEvent-Driven Architecture ExperienceData Modeling Across DatabasesTechnical Design Documentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringLLM Output EvaluationsNLP Pipeline MaintenanceData ModelingEvent-Driven ServicesAsynchronous ProgrammingTechnical WritingCode ReviewSemantic Search IntegrationAgentic Coding Tools

Soft Skills

Clear CommunicationCollaborationFeedback Reception

Tools & Technologies

Claude CodeCursorGitHub CopilotAzureAWSPostgreSQLMongoDBNeo4jTemporalDurable Task Scheduler

Industry Keywords

Insurance TechnologyNLPEvent SourcingIdempotencyRelational DatabasesDocument DatabasesGraph Databases

Tech Stack

Tools & technologies

AWSAzureMongoDBNeo4jPostgresPythonTypeScript

About the role

Key responsibilities & impact

Build and ship LLM-powered features and agentic workflows for insurance customers
Scope problems with product managers and data scientists, deliver features through production, and define success metrics
Write evaluations, guardrails, and feedback loops with explicit token and latency budgets
Review agent-generated code for correctness, security, and design issues
Maintain and extend NLP pipelines converting unstructured claim data into structured customer-actionable data
Build and operate durable event-driven services with deterministic workflows, retries, checkpointed model outputs, and idempotency
Trace model calls and agent steps for reconstruction, auditing, source-document citations, and alerting
Model and query claims data across relational, document, and graph stores
Design tenant isolation, least-privilege agent/tool access, and model-provider data controls
Write technical design documents and secure team feedback before significant changes
Participate in a shared on-call rotation
Own features end to end from concept through production

Requirements

What you’ll need

3+ years of professional software engineering experience, including at least one LLM-powered feature shipped and operated in production
Python and TypeScript: typed, tested, async code in both, with real depth in one
Designed LLM output evaluations and shipped guardrails
Daily production use of Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools, with ability to constrain context and verify output
Experience blending LLMs with semantic search and classical NLP, including structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM
Experience with message- or event-driven architectures, long-running workflows, retries, idempotent handlers, event-sourced state, and an LLM or agent step
Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j
Backend services operated on Azure or AWS, with exposure to Temporal or Durable Task Scheduler
Experience writing technical design documents and obtaining team feedback and buy-in before implementation
Clear technical and non-technical writing and discussion skills; able to give and receive code review

Benefits

Comp & perks

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