Senior AI Engineer
Careers Leftfieldlabs, Remote
What you will do
We are seeking a Senior AI Engineer to design, build, and ship the AI-powered features at the core of the illumend platform. This is a hands-on engineering role: you will write production code every day, using modern AI development tools to move quickly in a fast-paced environment while keeping quality, security, and reliability high.
illumend works in a regulation-heavy space. Insurance policies, certificates, and contract requirements are dense with detailed rules. Your job is to build AI systems that handle that complexity behind the scenes so customers get simple, accurate results.
- Build and ship production AI features end to end, such as extracting and validating data from insurance documents, checking coverage against contract requirements, and AI assistants and agents that help users act on what they find
- Design LLM pipelines and integrations (prompting, structured outputs, tool use, retrieval) across Python/FastAPI backend services and React/TypeScript frontends
- Build evaluation sets and automated checks to measure accuracy, catch regressions, and improve model output over time, and monitor quality, latency, and cost in production
- Fully embed AI development tools (e.g., Claude Code, Cursor, GitHub Copilot) into your daily workflow to accelerate coding, refactoring, test generation, prototyping, and documentation, while reviewing and validating everything you ship
- Build fast, functional prototypes to test new AI capabilities, then iterate and harden them for production
- Dig into raw customer documents, data, edge cases, and API specs rather than relying on secondhand information
- Make pragmatic technical decisions that put stability, security, and ROI ahead of novel or overly complex tech
Required Skills
What you need
- Senior-level experience building production web applications, with strong Python (FastAPI) skills and working knowledge of React, TypeScript, Next.js, and PostgreSQL
- Hands-on experience shipping LLM-powered features to production, including prompt design, structured outputs, tool use and agents, and retrieval
- Experience evaluating AI output: building test sets, measuring accuracy, and handling failure cases such as hallucinations and low-confidence results
- Experience extracting structured data from unstructured documents (PDFs, scanned forms) is a strong plus
- Mastery of AI coding assistants and agents in daily engineering work, backed by a clear method for reviewing and validating their output
- Ability to quickly learn a complex, regulation-heavy B2B domain; insurance experience is a plus
- A strong commitment to engineering standards, maintainability, and security, balanced with business pragmatism