AI Engineer

Role overview Build and operate AI features and automation for product and internal systems, turning established architecture patterns into reliable production software. The work centers on Python services and integrations using large language models and retrieval, with collaboration across engineering, data, security, product, and operations teams.

Responsibilities - Develop and maintain Python services, pipelines, and integrations that apply LLMs and retrieval to practical product and internal needs. - Integrate LLM APIs using agreed approaches to model selection, cost, evaluation, testing, and failure handling. - Follow multi-tenant data isolation and protected health information boundaries when implementing AI capabilities. - Work with data and analytics partners on retrieval-backed features such as semantic search, summarization, and contextual guidance. - Contribute reusable prompts, evaluation methods, reference implementations, documentation, and observability for AI systems. - Support production operations, incident response, and feedback loops; monitor quality, usage, and cost.

Requirements - 3–5 years of software engineering experience, including at least one year on AI- or ML-backed systems and a contribution to an LLM system in production. - Strong Python skills for production services, data pipelines, and integrations. - Working knowledge of LLM orchestration, evaluation frameworks, and agent or tool-using systems, including secure enterprise API connections. - Experience with retrieval-augmented systems and familiarity with enterprise data platforms and cloud environments such as Databricks, Azure, or AWS. - Familiarity with CI/CD, infrastructure as code, and MLOps practices; clear written and verbal communication. - Bachelor’s or master’s degree in computer science, engineering, data science, or a related field, or equivalent relevant preparation is not specified.

Nice to have - Production experience in a regulated industry and familiarity with HIPAA, SOC 2, or NIST controls, multi-tenant SaaS isolation, and B2B identity and access patterns. - Experience using generative AI tools to support engineering work.

Benefits and work setup Remote role, with preference for candidates on the US East Coast. The role includes participation in an on-call rotation.