Senior Python AI/ML Engineer – Azure Databricks

Location: Remote

Experience: 10+ years

About the role: We’re looking for a senior Python AI/ML engineer to lead the development of secure, production-ready AI applications for a healthcare payer organization. You’ll build Python services, machine learning solutions, and AI agents, and provide technical leadership for Azure Databricks Lakehouse products. The work includes healthcare data and medical records, so experience delivering reliable, privacy-conscious solutions in regulated environments is valuable. The ideal candidate has deep Python engineering experience, a strong track record bringing ML and AI systems into production, and hands-on experience with Azure Databricks. Experience applying or adapting small language models (SLMs) to medical records is a strong plus.

What you’ll do: Design and deliver AI agents and ML-enabled applications for healthcare payer workflows. Build production-quality Python services, APIs, orchestration components, and reusable libraries. Develop, evaluate, deploy, and monitor ML, NLP, LLM, and SLM solutions. Design RAG, tool-calling, multi-agent, guardrail, and human-in-the-loop workflows. Lead data pipeline and Lakehouse development using Azure Databricks, Spark, and Delta Lake. Build document processing workflows, including OCR, extraction, search, classification, and summarization. Set standards for evaluating AI quality, safety, performance, cost, and reliability. Apply MLOps, CI/CD, testing, monitoring, security, and privacy practices. Partner with engineering, data, clinical, security, product, and business teams. Mentor developers and guide technical designs, reviews, and engineering standards. What you’ll bring 10+ years in professional software development, including 7+ years of advanced Python development.3–4+ years building and operating ML, NLP, generative AI, or agentic AI solutions. Hands-on experience with LLM or SLM applications, RAG, embeddings, vector search, tool calling, and evaluation.4+ years building Azure solutions, including 3+ years with Azure Databricks or a comparable Lakehouse platform. Strong experience with Spark, Delta Lake, distributed processing, and data pipelines. Knowledge of the ML lifecycle, including feature engineering, model evaluation, deployment, and monitoring. Experience with structured and unstructured data, APIs, documents, and large datasets. Strong software delivery skills across Git, CI/CD, automated testing, code review, and production support. Technical leadership, mentoring, and clear communication across engineering and business teams. A relevant bachelor’s or master’s degree, or equivalent practical experience.

Preferred: Experience adapting or deploying SLMs or language models for medical records or clinical documents. Familiarity with healthcare payer data, medical terminology, coding systems, or HL7 FHIR.Experience with MLflow, Databricks Model Serving, Mosaic AI, or similar MLOps tools. Knowledge of HIPAA-aligned engineering, PHI handling, de-identification, and responsible AI.Experience with Docker, Kubernetes, Azure DevOps, Terraform, or similar tools.