AI Engineering Lead

About the role

The Lead AI Engineer will design, build, and operate Ochsner's machine‑learning and conversational AI platform that powers automated patient and customer interactions. This hybrid role combines strategic planning with hands‑on technical leadership in a HIPAA‑regulated healthcare environment.

Key responsibilities

• Define AI/ML engineering strategy, standards, and roadmaps, translating product and business goals into multi‑quarter engineering plans.
• Direct teams across data ingestion, feature computation, model training, evaluation, packaging, deployment, and inference.
• Implement model lifecycle management, governance, experiment tracking, versioning, and rollback procedures.
• Build and scale feature stores, model registries, and training/inference platforms while optimizing cost, latency, and reliability.
• Collaborate with Product, Risk, Legal, and Compliance to document model intent, limitations, and audit artifacts for HIPAA compliance.

Required profile

• 8+ years of software/ML engineering experience, including at least 3 years in technical leadership.
• Experience productionizing machine‑learning or conversational AI systems in a regulated, HIPAA‑relevant environment.
• Strong stakeholder management, ability to translate technical concepts for non‑technical executives, and high ownership in ambiguous settings.

Required skills

• Machine learning, NLP, conversational AI, retrieval‑augmented generation, large language models.
• AWS services (SageMaker, Bedrock) or comparable cloud platforms.
• SQL and modern data platforms such as Snowflake or Databricks.
• MLOps tooling, CI/CD pipelines, containers, and infrastructure automation.
• Experience with LLMs, generative AI applications, prompting, evaluation, and fine‑tuning.