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 cases
- Build, deploy, and optimize multi-agent systems involving planning, reasoning, orchestration, tool usage, and memory management
- Drive 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 APIs
- Design and optimize scalable ETL / ELT pipelines (batch and streaming) to power AI, ML, and GenAI workflows
- Ensure data quality, lineage, freshness, and governance for AI-driven applications

AI Architecture, Optimization & Governance

- Define architecture patterns, guardrails, and governance frameworks for enterprise Agentic AI
- Optimize agent workflows through prompt engineering, tool selection, orchestration strategies, and memory design
- Define approaches for context management, token efficiency, latency optimization, and cost control
- Ensure 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 solutions
- Mentor and lead cross-functional teams across Data Engineering, AI/ML, and Application Engineering
- Participate inclient 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 solid foundation in Data Engineering, evolving into AI / GenAI delivery roles
- Proven 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 SQL
- Hands-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 equivalent
- Real-world implementation of multi-agent systems and autonomous workflows
- Experience building RAG-based, tool-integrated AI solutions
- Practical knowledge of model fine-tuning / adaptation techniques
- Strong understanding of:
- Prompt engineering
- LLM orchestration and tool usage
- Memory handling, agent context, and workflow optimization

Skills That Give You an Edge

- Experience with enterprise-scale AI transformations, preferably in Life Sciences / Pharma
- Exposure to LLMOps / MLOps (monitoring, evaluation, governance, drift detection)
- Strong understanding of AI evaluation, guardrails, and Responsible AI practices
- Ability totranslate 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

📌 Associate Director (10826) (India)
🏢 Axtria - India
📍 India