AI Lead (8-12 yrs)

Role and Responsibilities:

- Client Advisory & AI Strategy: Serve as a trusted advisor to clients and senior stakeholders, helping define and execute enterprise AI, Generative AI, and Agentic AI strategies.

- End-to-End Delivery: Lead the delivery of enterprise GenAI use cases from ideation through production deployment, ensuring scalability, security, governance, and business value realization.

- AI Governance & Responsible AI: Establish AI governance, model evaluation, prompt management, guardrails, monitoring, and responsible AI practices.

- Cross-functional Leadership: Collaborate with business stakeholders, data engineers, analytics teams, and solution architects, to drive technical excellence, innovation, and AI-powered business outcomes.

Qualifications:

- Educational Background: Master's or Bachelor's in computer science, engineering, mathematics, or related fields from top-tier institutions.

- Experience: 7+ years of experience in Data & AI, including 3+ years leading Generative AI initiatives.

- Proven experience delivering enterprise-scale AI/ML and GenAI solutions from concept to production.

- Technical Skills: Proficiency in Python, PySpark and SQL.

- Strong expertise in Databricks Generative AI capabilities, including Mosaic AI, AI Gateway, Vector Search, Foundation Models, Model Serving, Agent Framework, MLflow and Unity Catalog for AI Governance.

- Hands-on experience with Large Language Models (GPT, Claude, Llama, Mistral, Gemini, etc.), Retrieval-Augmented Generation (RAG), AI Agents and Agentic Workflows, Prompt Engineering, Vector Databases and Semantic Search, Model Evaluation and AI Observability, Responsible AI, Guardrails, and Governance.

- Strong expertise in Databricks Data Engineering capabilities, including Databricks Lakehouse Architecture, ETL/ELT Design and Development, Delta Lake, Data Modeling, Batch and Streaming Data Pipelines, Data Quality and Data Governance (Highly Preferred).

- Familiarity with MLOps and LLMOps practices, CI/CD, monitoring, and automated testing.

- Certifications: Relevant certifications in AI and machine learning, such as Databricks Certified Generative AI Engineer Associate/Professional, or similar (Preferred not mandatory).

- Leadership: Demonstrable leadership ability, with experience managing and mentoring teams.

- Problem-Solving: Superior problem-solving skills, with a track record of delivering innovative generative AI solutions.

- Communication: Excellent communication and presentation skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

- Industry Knowledge: Deep understanding of industry trends and challenges in generative AI and machine learning.

- Stakeholder Management: Experience engaging with senior business stakeholders and translating business requirements into AI solutions.