Associate Director - Data and AI

Job Purpose

We are seeking a highly motivated and skilled AI Engineer to join our team and drive innovation in the fast-evolving landscape of Generative AI. The ideal candidate will have deep hands-on expertise in RAG (Retrieval-Augmented Generation) pipelines and working familiarity with Frontier Models (e.g., GPT-4, Claude, LLaMA, etc.). Exposure to cutting-edge orchestration frameworks like CrewAI, LangGraph, Autogen, or OpenAI SDK is highly desirable.

You will work closely with product, data, and engineering teams to prototype, build, and scale AI-first solutions that deliver tangible business impact. Strong communication skills are key, as you’ll be working with cross-functional teams and occasionally interfacing with clients.

Location : Bangalore (Hybrid Work Model, 4 day work from office)

Experience : 15+ years

1. Product Leadership & Domain Execution
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 all data and AI products strictly adhere to US Healthcare standards and regulations (HIPAA, HITRUST, SOC2, PHI/PII handling).

2. AI Engineering & Solution Architecture
Architect and oversee the implementation of Generative AI applications, RAG (Retrieval-Augmented Generation) pipelines, and autonomous agentic workflows.
Design robust orchestration systems using modern frameworks such as LangChain and LangGraph.
Evaluate and integrate state-of-the-art foundation models (including Anthropic Claude, Azure OpenAI models, and open-source alternatives).
Implement robust AI Guardrails (content safety, hallucination detection, prompt injection defense) to guarantee compliance, safety, and deterministic behavior in clinical or operational workflows.

3. Data Platform & Infrastructure
Lead data architecture efforts leveraging Databricks (Delta Lake, Unity Catalog) and the Microsoft Azure tech stack.
Oversee scalable ETL/ELT pipelines, data modeling, and data integrations involving healthcare data standards (FHIR, HL7, EHR data).
Collaborate with data engineering teams to optimize lakehouse performance, query speed, and storage efficiency.

4. Data & AI Governance, Security, and AIOps
Establish enterprise-wide Data & AI Governance practices, including data lineage, cataloging, access controls, and model explainability.
Build and scale AIOps & MLOps operational frameworks to ensure continuous monitoring, prompt logging, drift detection, model evaluation, and cost optimization.

Work closely with Information Security and Regulatory teams to ensure compliance across all data pipelines and AI deployments.

AI & LLM Engineering:

Demonstrated hands-on experience with LLM orchestration frameworks (LangChain, LangGraph).

Direct experience working with advanced foundation models (e.g., Anthropic Claude, GPT-4) via APIs or cloud deployments.

Deep understanding of guardrailing tools and techniques (NVIDIA NeMo Guardrails, Llama Guard, Guardrails AI, or custom validation pipelines).

AIOps & MLOps: Proven track record in operationalizing AI systems—including monitoring, evaluation frameworks (RAGAS, TruLens), observability, and prompt versioning.

Leadership & Communication: Excellent stakeholder management skills with the ability to articulate complex technical and AI concepts to non-technical business leaders.

Preferred / Nice-to-Have Skills

Experience with healthcare interoperability standards (FHIR, HL7).
Hands-on experience with vector databases (Pinecone, Qdrant, Azure AI Search, Databricks Vector Search).

Certifications: Azure Solutions Architect, Databricks Certified Data Engineer / Machine Learning Professional, or Scrum Product Owner.