Senior AI Engineer

CCC Intelligent Solutions

. Own delivery of LLM-powered systems in Python and TypeScript from ambiguous customer problem through production operation .

Posted 9/17/2026full-timeRemote • Illinois • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and delivering LLM-powered systems using Python and TypeScript, with a strong focus on designing NLP pipelines and establishing security baselines. Proven ability to mentor engineers and communicate effectively with both technical and non-technical audiences.

Highest-signal resume keywords

LLM-Powered System ArchitecturePython and TypeScript ExpertiseNLP Pipeline DesignEvent-Driven System DevelopmentCI/CD and Infrastructure as Code

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptNLP Pipeline DesignEvent-Driven SystemsPostgreSQLMongoDBAzureAWSCI/CDDurable Workflow Engine

Soft Skills

Clear WritingTechnical CommunicationMentoring

Tools & Technologies

Claude CodeCursorGitHub CopilotTemporalDurable Task SchedulerLangGraphMicrosoft Agent FrameworkOpenTelemetry

Industry Keywords

InsuranceClaimsAutomotive Repair

Tech Stack

Tools & technologies

AWSAzureMicroservicesMongoDBNeo4jPostgresPythonReactSQLTypeScript

About the role

Key responsibilities & impact

Own delivery of LLM-powered systems in Python and TypeScript from ambiguous customer problem through production operation
Scope problems with product managers and data scientists
Set evals and guardrails strategy, release gates, production signals, and historical-claims simulations
Establish standards for agentic coding tools, including specifications, instruction files, hooks, permission policies, and code review
Design NLP pipelines that turn unstructured claim data into structured customer-actionable data
Choose where semantic search, classical NLP, or an LLM fits
Build and operate durable, event-driven, multi-tenant systems with agents as steps inside deterministic workflows
Design failure modes, replay semantics, and cost profiles
Own tracing and audit so model calls and agent steps can be reconstructed and cited to sources
Own claims-data modeling and handling across relational, document, and graph stores
Establish privacy and security baselines, including tenant isolation, least-privilege access, redaction, retention, and personal/medical data controls
Author complex-system design documents and review other engineers' designs and code
Mentor engineers
Participate in a shared on-call rotation
In the first six months, gate model changes with evals, catch regressions before customers see them, and demonstrate accuracy outcomes

Requirements

What you’ll need

6+ years of professional software engineering experience
Architected, shipped to external customers, and carried through at least one model or prompt migration an LLM-powered system
Python and TypeScript expertise, including async model, typing strictness, test strategy, and performance profiling
Experience setting evals and guardrails strategies for a product area
Daily production use of Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools
Experience designing pipelines blending LLMs, semantic search, and classical NLP
Experience designing durable, event-driven systems with deterministic orchestration around non-deterministic model steps
Experience with compensating actions, idempotency, backpressure, and event-sourced replay
Production experience with stores such as PostgreSQL, MongoDB, Neo4j, SQL Server, or Cosmos DB
Experience architecting and operating systems on Azure or AWS
Experience with CI/CD and infrastructure as code
Hands-on experience with a durable workflow engine such as Temporal or Durable Task Scheduler
Authored technical design documents for systems spanning more than one team
Clear writing and discussion for technical and non-technical audiences
React and TypeScript experience preferred
Experience with LangGraph, Microsoft Agent Framework, MCP, A2A, command-line tools, and microservices preferred
Experience with LangSmith, Arize, Braintrust, and OpenTelemetry-based tracing preferred
Experience designing A/B tests for AI features preferred
Exposure to insurance, claims, or automotive repair domains preferred
A video interview is required
Candidates are not permitted to use generative AI or automated assistance during interviews unless explicitly allowed

Benefits

Comp & perks

This position is bonus and/or commission eligible
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