AI/ML Engineer - Patient Document Vector Store

Required 8+ years of experienced AI/ML Engineer to design and operationalize an enterprise-scale Patient Document Vector Store. This role will build secure, reusable ingestion pipelines and enable advanced retrieval augmented generation (RAG) across billions of patient documents., * Build and manage streaming & batch ingestion pipelines for patient documents.

• Design and host the enterprise vector store with secure API access and audit logging.
• Execute large-scale data loads (11M patients / 1.5B documents).
• Implement observability, QA automation, and monitoring dashboards.
• Collaborate with cross-functional teams to ensure compliance with healthcare standards.

• Expertise in AI/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain).
• Experience with vector databases (Pinecone, Weaviate, Milvus, FAISS).
• Strong knowledge of RAG, hybrid retrieval, distributed systems, and cloud platforms (AWS/Azure/Google Cloud Platform).
• Familiarity with Kubernetes, API gateways (Apigee), and healthcare compliance (HIPAA/PHI).
• Proven ability in monitoring, observability, and QA automation.

Preferred

• Experience with large-scale document ingestion pipelines.
• Background in healthcare data platforms and interoperability standards.
• Knowledge of audit logging frameworks and lineage tracking.