Senior AI Engineer - Data Scientist

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Job Description:

We’re seeking a Senior AI Engineer / Data Scientist to lead the design, deployment, and scaling of enterprise AI capabilities—specifically large language model (LLM) solutions, LLMOps practices, and the development of a healthcare ontology/knowledge graph to enhance a complex data environment.

Responsibilities

• Ontology & Knowledge Graph

• Design and maintain a healthcare ontology to normalize CMS data across claims, providers, and workflows.

• Build and manage knowledge graphs (RDF/OWL or property graph) to support semantic search, inference, and RAG augmentation.

• Develop graph data pipelines for ingestion, transformation, and entity resolution aligned with governance standards.

• Collaborate with SMEs to define controlled vocabularies and create reusable semantic APIs for analytics and AI.

• GenAI & LLMOps

• Architect and operationalize LLMs for production use cases including RAG, agentic workflows, and MCP tools.

• Build LLM evaluation and safety frameworks (prompt quality, grounding, hallucination detection, bias checks) with automated testing and human-in-the-loop reviews.

• Design cost- and latency-aware pipelines with observability for performance and reliability.

• Implement LLMOps best practices: prompt versioning, CI/CD for artifacts, rollout strategies, and A/B testing.

• Integrate vector databases and optimize chunking, embeddings, and retrieval for high-quality responses.

• Platform & System Architecture

• Support productionalization of AI/ML workflows with automated quality checks and lifecycle orchestration.

• Ensure data security, governance, and CMS compliance.

• Contribute to high-level system design for integrating new AI capabilities into a cloud-based analytics platform.

• Maintain documentation and acceptance criteria for system changes.

Basic Qualifications

• Education/Experience: 10+ years with BS/BA; 8+ years with MS/MA; 5+ years with PhD in Computer Science, Data Science, or related field.
• Hands-on experience with LLMs and GenAI solutions, including prompt engineering, RAG architecture, and LLMOps practices.
• Proven experience in ontology design and knowledge graph development for complex data-driven systems.
• Experience with Databricks, Snowflake, and AWS Cloud Services.
• Proficiency in Python and SQL (Snowflake SQL).
• Experience with CI/CD workflows and automated deployments.
• Familiarity with Scaled Agile Framework (SAFe).
• Excellent communication skills and ability to work independently.
• ship required.

Preferred Qualifications

• Experience with Databricks E2 components (Unity Catalog, Feature Store).
• Knowledge of CMS systems and Medicare/Medicaid data.
• Familiarity with LLM/GenAI tooling (LangChain, LlamaIndex, Hugging Face, AWS Bedrock).
• Experience with vector databases and RAG orchestration.
• Knowledge graph tools: Neo4j, TigerGraph, AWS Neptune, RDF/OWL, SPARQL, Gremlin, Cypher, Protégé.
• Model lifecycle & governance: MLflow, Model Registry, feature stores, LLM safety testing.
• Observability & automation: GitHub Actions/Jenkins, Terraform, Docker/Kubernetes, PrometheGrafana.