Senior AI Engineer

Role overview

Lead production AI workflow projects for several clients at a time, taking each from discovery and system design through implementation, launch, and ongoing monitoring. The work combines hands-on engineering with architectural decisions, production support, and mentoring junior engineers.

Responsibilities - Design and build AI systems using workflow automation, Python services, and large language model APIs. - Choose when to use existing workflow tools, custom code, or model fine-tuning to meet project needs. - Add logging, tracing, drift detection, cost tracking, and alerts to production workflows. - Diagnose issues involving model behavior, integrations, and data quality. - Review code and architecture, and mentor junior engineers through regular one-to-ones. - Improve shared workflow components, evaluation tools, and prompt libraries.

Requirements - At least five years of software engineering experience, including two or more years with AI, machine learning, or LLM-powered systems. - Production experience with a major LLM provider or self-hosted open-source models. - Strong Python skills, including asynchronous programming, type hints, testing, and package management; familiarity with a framework such as FastAPI, Pydantic, LangChain, or LlamaIndex. - Experience with workflow tools such as n8n, Make, Zapier, or Temporal, and sound judgment about when to use them. - Experience with embeddings and vector databases such as pgvector, Pinecone, Qdrant, or Weaviate. - Ability to evaluate and troubleshoot variable model outputs using techniques such as prompt design, evaluation harnesses, or A/B testing. - Clear written communication for architecture documents, incident reviews, and client reports.