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EvolutionIQ

AI-driven SaaS for insurance claims handling

Senior AI Engineer - Agentic

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeChicago, IL, USA$180k - $225kIn-person

About the Job

Requirements

  • Six or more years of professional software engineering experience, including architecting and shipping an LLM-powered system to external customers and carrying it through at least one model or prompt migration.
  • Expert-level Python and TypeScript skills, including setting conventions for asynchronous programming, typing strictness, and test strategy in a shared codebase, and profiling and fixing a performance issue.
  • Experience establishing an evaluations and guardrails strategy for a product area, including deciding when human approval is required and how production corrections feed back into evaluations.
  • Experience using Claude Code, Cursor, GitHub Copilot, or similar agentic coding tools for production work, constraining their context, verifying output, and identifying and rejecting unsuitable changes.
  • Experience designing pipelines combining large language models, semantic search, and classical natural language processing, including defensible retrieval design and an example where a classical technique outperformed a large language model on cost, latency, or reliability.
  • Experience designing durable, event-driven systems with deterministic orchestration around non-deterministic model steps, including compensating actions, idempotency, backpressure, and event-sourced replay.
  • Experience modeling data and developing across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including choosing when each type fits and making partition-key, consistency, and tenant-isolation decisions.
  • Experience architecting and operating systems on Azure or AWS, using continuous integration/continuous delivery and infrastructure as code, and hands-on experience with a durable workflow engine such as Temporal or the Durable Task Scheduler.
  • Experience authoring technical design documents for systems spanning multiple teams, using them to obtain feedback and buy-in before implementation, and having those teams build to them.
  • Ability to communicate clearly in writing and discussion with technical and non-technical audiences, elicit customers’ actual problems, and explain trade-offs.

Responsibilities

  • Own delivery of LLM-powered systems in Python and TypeScript, from ambiguous customer problem definition with product managers and data scientists through production operation.
  • Set the evaluations and guardrails strategy for the area, including release gates, production signals, and simulations of changes against historical claims before release.
  • Improve how the team uses agentic coding tools by refining specifications, instruction files, hooks, and permission policies, and reviewing generated code to the same standard before it is merged.
  • Design natural language processing pipelines that transform unstructured claim data into actionable structured data, selecting between semantic search, classical natural language processing, and large language models.
  • Build and operate durable, event-driven, multi-tenant systems where agents run as steps in deterministic workflows, designing failure modes, replay semantics, and cost profiles ahead of production load.
  • Own tracing and audit for the area, recording every model call and agent step so recommendations can be reconstructed and cited to their sources by on-call staff and auditors.
  • Set the privacy and security baseline for systems in the area, including tenant isolation, least-privilege access for agents and tools, redaction, retention, and rules for data sent to model providers.
  • Author design documents for complex systems to obtain feedback and buy-in, review engineers’ designs and code, and mentor engineers in the area.
  • Participate in a shared on-call rotation for the systems owned.

Desired Qualifications

  • Experience with React and TypeScript to deliver full-stack features, especially chat, streaming, and citation-heavy AI experiences.
  • Experience with agent frameworks such as LangGraph, PydanticAI, and the Microsoft Agent Framework, and agent tool access methods including the Model Context Protocol, Agent2Agent protocol, command-line tools, and microservices.
  • Experience with large language model observability and evaluation tools such as LangSmith, Arize, or Braintrust, and OpenTelemetry-based tracing.
  • Experience designing A/B tests for AI features.
  • Exposure to insurance, claims, or automotive repair domains.

About the Company

EvolutionIQ

AI-driven SaaS for insurance claims handling

EvolutionIQ provides AI-driven software for insurers to streamline claims handling across Disability, Workers' Comp, and General Liability. The platform analyzes claim data and medical information, predicts claim paths earlier, automatically routes complex cases to the right expert teams, and guides examiners on needed actions via a SaaS model. It differentiates itself by using AI to understand bodily injury data with precision and to forecast returns-to-work, enabling proactive prioritization unlike traditional manual-rule systems. Its goal is to speed and improve accuracy of claims processing to increase return-to-work outcomes and overall insurer efficiency.

Company size
201-500
Company stage
Acquired
Total funding
$60.3M
Headquarters
New York City, New York
Founded
2019

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