Senior AI Engineer (LLM & Applied ML)

Role overview

An applied AI engineering role focused on embedding language models into production business software rather than demo prototypes. Work centers on integrating models into existing web products while treating prompts, guardrails, latency, and cost as engineering problems with measurable outcomes.

Responsibilities

- Integrate large language models into backend and front-end product surfaces, including intelligent search, document processing, workflow automation, and agent-style assistant experiences inside customer-facing portals. - Define and enforce guardrails, evaluation metrics, and quality benchmarks that go beyond anecdotal checks. - Optimize for latency, throughput, and provider spend as usage scales across customer accounts. - Instrument pipelines with structured logging so every model call can be traced, audited, and reproduced. - Collaborate with security and platform teams on PII boundaries, data handling policies, and documented failure modes.

Requirements

- Strong Python skills with hands-on experience shipping LLM-backed features, not just prototyping them. - Comfort working across a typical web stack (a backend framework plus a modern front-end framework) and integrating hosted model providers or comparable alternatives. - Familiarity with vector stores, retrieval patterns, background job systems, and the operational side of model calls. - Practical prompt engineering experience treated as a measurable discipline rather than intuition. - Track record of collaborating with cross-functional partners on data, privacy, and reliability concerns.

Nice to have

- Prior work on AI features that real users rely on, with evidence of iteration driven by observed behavior.