Manager - BIM

We are seeking senior Data Engineering leaders who have evolved into handson 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.

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 in client discussions, roadmap definition, solutioning, proposals, and Agentic AI thought leadership

Core Background (NonNegotiable)

• 12+ years of experience with a strong 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 to translate business problems into scalable, governed AI solutions