Required Qualifications & Skills

- 16–20 years of experience across BI, analytics architecture, data platforms, enterprise reporting, AI-enabled analytics, solution consulting, or digital transformation.
- Robust architecture and hands-on expertise in Power BI and at least one additional BI platform, such as Tableau, ThoughtSpot, Qlik, MicroStrategy, or Looker.
- Experience with Microsoft Fabric, Snowflake, Databricks, Azure/AWS, SQL, dimensional modeling, semantic models, DAX, performance tuning, data governance, and deployment lifecycle management.
- Deep understanding of GenAI and Agentic AI, including LLMs, RAG, vector search, embeddings, prompt engineering, model evaluation, tool use, memory, orchestration, multi-agent workflows, and human-in-the-loop controls.
- Practical experience rolling out AI applications, copilots, AI assistants, decision-support platforms, conversational analytics, or autonomous workflow agents in production environments.
- Ability to integrate AI capabilities with enterprise data, APIs, business applications, BI platforms, knowledge bases, workflow tools, and security/identity frameworks.
- Strong stakeholder management and executive communication skills,



with the ability to simplify technical architecture into business value narratives.

Preferred Qualifications

- Experience in pharma/life sciences analytics across commercial, medical, market access, field insights, omnichannel, launch performance, or executive reporting.
- Exposure to LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, Azure AI Foundry, Copilot Studio, Azure OpenAI/OpenAI, AWS Bedrock, Google Vertex AI, Pinecone, Weaviate, or similar platforms.
- Experience in AI governance, responsible AI, model monitoring, cost optimization, telemetry, prompt safety, explainability, and production support models.
- Experience in pre-sales, RFP/RFI solutioning, technical proposals, estimates, demos, reusable accelerators, and thought leadership.

Success Metrics

- Quality, scalability, performance, security, and adoption of BI and AI solution architectures.
- Successful movement of AI-enabled analytics solutions from concept to production, with measurable usage and business impact.
- Maturity of agentic solution patterns, RAG designs, governance controls, observability, and human-in-the-loop processes.
- Reusable accelerators, reference architectures, demo assets, and team enablement.

📌 Gen AI BI Director (Gurugram)
🏢 Axtria - Ingenious Insights
📍 Gurugram