Associate Director

Position Summary

We are seeking senior Data Engineering leaders who have evolved into hands‑on GenAI / Agentic AI practitioners. This role is not for pure research, academic, or experimentation-focused profiles. The expectation is production-grade delivery, grounded in strong data engineering fundamentals and scaled enterprise systems.

Job Responsibilities

Lead Agentic AI Delivery at Enterprise Scale

Lead end-to-end architecture, design, and production deployment of Agentic AI solutions for complex enterprise and Life Sciences use casesBuild, deploy, and optimize multi-agent systems involving planning, reasoning, orchestration, tool usage, and memory managementDrive GenAI implementations beyond POCs into stable, scalable, and observable production systems

Deep Integration with Enterprise Data Platforms

Architect and integrate Agentic AI systems with Databricks, data lakes, data warehouses, streaming platforms, and enterprise APIsDesign and optimize scalable ETL / ELT pipelines (batch and streaming) to power AI, ML, and GenAI workflowsEnsure data quality, lineage, freshness, and governance for AI-driven applications

AI Architecture, Optimization & Governance

Define architecture patterns, guardrails, and governance frameworks for enterprise Agentic AIOptimize agent workflows through prompt engineering, tool selection, orchestration strategies, and memory designDefine approaches for context management, token efficiency, latency optimization, and cost controlEnsure reliability, observability, security, and performance of AI systems in production

Leadership & Stakeholder Engagement

Partner with business stakeholders to identify high-impact AI use cases and translate them into scalable solutionsMentor and lead cross-functional teams across Data Engineering, AI/ML, and Application EngineeringParticipate in client discussions, roadmap definition, solutioning, proposals, and Agentic AI thought leadership

Education

BE/B.Tech

Master of Computer Application

Work Experience

Core Background (Non‑Negotiable)

12+ years of experience with a strong foundation in Data Engineering, evolving into AI / GenAI delivery rolesProven experience delivering production-grade GenAI / Agentic AI solutions in real enterprise environments (Candidates limited to academic, research, or POC-only experience are not suitable)

Data Engineering Excellence

Deep expertise in Databricks (PySpark, Delta Lake, workflows, optimization)Extensive experience designing, building, and scaling ETL pipelines (batch and streaming)Strong programming skills in Python and SQLHands-on experience with cloud platforms (AWS, Azure, or GCP)

Agentic AI & GenAI Capabilities

Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or equivalentReal-world implementation of multi-agent systems and autonomous workflowsExperience building RAG-based, tool-integrated AI solutionsPractical knowledge of model fine-tuning / adaptation techniquesStrong understanding of:Prompt engineeringLLM orchestration and tool usageMemory handling, agent context, and workflow optimization

Skills That Give You An Edge

Experience with enterprise-scale AI transformations, preferably in Life Sciences / PharmaExposure to LLMOps / MLOps (monitoring, evaluation, governance, drift detection)Strong understanding of AI evaluation, guardrails, and Responsible AI practicesAbility to translate business problems into scalable, governed AI solutions

Behavioural Competencies

Teamwork & Leadership

Motivation to Learn and Grow

Ownership

Cultural Fit

Technical Competencies

Problem Solving

Lifescience Knowledge

Communication

Project Management

Capability Building / Thought Leadership

Databricks

PySpark

Python