Gen AI BI Director

Axtria - Ingenious Insights; Gurugram District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Axtria - Ingenious Insights is seeking a seasoned analytics architect to lead BI strategy and AI-enabled architectures in enterprise environments. You will shape data platforms and reporting frameworks, integrating Power BI with other BI tools and AI copilots.

The role emphasizes governance, scalability, and business-value storytelling to executives. The ideal candidate will demonstrate extensive experience across BI domains, strong stakeholder management, and hands-on deployment of GenAI

Qualifications

• 16–20 years of experience across BI, analytics architecture, data platforms, enterprise reporting, AI-enabled analytics, solution consulting, or digital transformation.
• Strong 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.

Skills

BI architecture

Executive communication

Stakeholder management

Analytics strategy

Data governance

Tools

Power BI

Tableau

ThoughtSpot

Qlik

MicroStrategy

Looker

Snowflake

Databricks

SQL

Job description

• 16–20 years of experience across BI, analytics architecture, data platforms, enterprise reporting, AI-enabled analytics, solution consulting, or digital transformation.
• Strong 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.