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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in leading the development and delivery of enterprise data platforms and AI/LLM-powered products, ensuring compliance with US Healthcare standards. Proficient in architecting scalable AI solutions and implementing robust data governance practices.
Highest-signal resume keywords
Enterprise Data Platforms LeadershipRAG Pipeline ExpertiseUS Healthcare Standards ComplianceGenerative AI Application ArchitectureData Governance Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
RAG PipelinesGenerative AIData ArchitectureETL/ELT PipelinesData ModelingAI GuardrailsHealthcare Interoperability StandardsFoundation ModelsVector DatabasesAI/LLM Product Development
Soft Skills
Strong CommunicationStakeholder Management
Tools & Technologies
LangChainLangGraphDatabricksMicrosoft AzureNVIDIA NeMo GuardrailsPineconeQdrantAzure AI SearchOpenAI SDKCrewAI
Certifications & Qualifications
Azure Solutions ArchitectDatabricks Certified Data EngineerMachine Learning ProfessionalScrum Product Owner
Industry Keywords
HIPAAHITRUSTSOC2PHIPIIFHIRHL7EHR
Tech Stack
Tools & technologiesAzureCloudETL
About the role
Key responsibilities & impact- Lead the strategy, roadmap, and delivery of enterprise data platforms and AI/LLM-powered products from conceptualization to production
- Drive product discovery and requirements with business stakeholders, translating workflows and pain points into scalable data and AI solutions
- Ensure data and AI products adhere to US Healthcare standards and regulations
- Architect and oversee Generative AI applications, RAG pipelines, and autonomous agentic workflows
- Design orchestration systems using frameworks such as LangChain and LangGraph
- Evaluate and integrate foundation models including Anthropic Claude, Azure OpenAI models, and open-source alternatives
- Implement AI guardrails for content safety, hallucination detection, and prompt injection defense
- Lead data architecture using Databricks and the Microsoft Azure technology stack
- Oversee scalable ETL/ELT pipelines, data modeling, and healthcare data integrations involving FHIR, HL7, and EHR data
- Optimize lakehouse performance, query speed, and storage efficiency with data engineering teams
- Establish enterprise-wide Data & AI Governance practices, including data lineage, cataloging, access controls, and model explainability
- Build and scale AIOps and MLOps frameworks for monitoring, prompt logging, drift detection, model evaluation, and cost optimization
- Collaborate with Information Security and Regulatory teams to ensure compliance
- Prototype, build, and scale AI-first solutions with product, data, and engineering teams
- Interface with clients occasionally and communicate complex technical concepts to business leaders
Requirements
What you’ll need- 15+ years of experience
- Deep hands-on expertise in RAG (Retrieval-Augmented Generation) pipelines
- Working familiarity with Frontier Models such as GPT-4, Claude, and LLaMA
- Exposure to orchestration frameworks such as CrewAI, LangGraph, Autogen, or OpenAI SDK
- Strong communication and stakeholder management skills
- Experience leading enterprise data platforms and AI/LLM-powered products from conceptualization to production
- Experience with US Healthcare standards and regulations, including HIPAA, HITRUST, SOC2, and PHI/PII handling
- Hands-on experience with LLM orchestration frameworks including LangChain and LangGraph
- Direct experience with advanced foundation models such as Anthropic Claude and GPT-4 via APIs or cloud deployments
- Deep understanding of AI guardrailing tools and techniques, including NVIDIA NeMo Guardrails, Llama Guard, Guardrails AI, or custom validation pipelines
- Proven experience operationalizing AI systems, including monitoring, evaluation frameworks such as RAGAS and TruLens, observability, and prompt versioning
- Experience with healthcare interoperability standards such as FHIR and HL7 preferred
- Hands-on experience with vector databases such as Pinecone, Qdrant, Azure AI Search, and Databricks Vector Search preferred
- Certifications such as Azure Solutions Architect, Databricks Certified Data Engineer / Machine Learning Professional, or Scrum Product Owner preferred
Benefits
Comp & perks- Hybrid work model
- 4 days of work from office