Head of Product

IDFC FIRST Bank, in partnership with Magna Hire, is looking for an experienced Lead Product Manager - Gen AI to drive the strategy, development, and adoption of AI-powered analytics products. This role will lead the end-to-end product lifecycle for Gen AI solutions, enabling conversational analytics, autonomous data agents, and intelligent decision-making across the organisation. The ideal candidate combines strong product management expertise with a deep understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, modern data platforms, and enterprise analytics.

The core responsibilities for the job include the following:

Product Strategy and Vision:

Define and own the long-term product vision and roadmap for Gen AI-powered analytics platforms.

Align AI capabilities with business priorities to drive measurable customer and business outcomes.

Build compelling business cases for AI investments and prioritise initiatives based on impact.

Gen AI Product Development:

Own the complete product lifecycle from ideation, Proof of Concept (PoC), MVP development, production rollout, and continuous optimisation.

Lead the development of conversational analytics products powered by LLMs, RAG, AI Agents, and enterprise knowledge systems.

Drive rapid experimentation while ensuring production readiness and scalability.

Agentic AI and Conversational Analytics:

Design and deliver intelligent AI agents capable of autonomous reasoning, planning, and data analysis.

Define product requirements for Retrieval-Augmented Generation (RAG), AI copilots, conversational interfaces, and autonomous workflows.

Embed conversational AI seamlessly into business and analytics workflows.

AI Platform and Data Integration:

Collaborate with engineering teams to integrate Gen AI products with Azure OpenAI, AWS Bedrock, enterprise data lakes, vector databases, BI platforms, and internal applications.

Drive product decisions around data ingestion, embeddings, prompting strategies, model orchestration, and AI infrastructure.

AI Governance and Responsible AI:

Ensure products leverage trusted enterprise data with strong governance, lineage, access controls, and security.

Define frameworks for AI safety, explainability, compliance, and responsible AI adoption.

Product Performance and Evaluation:

Establish product success metrics covering AI response quality, Accuracy and hallucination rates, Latency, Cost optimization, User adoption, and Business impact.

Continuously optimise models, prompts, and user experiences using feedback and experimentation.

Stakeholder Management:

Partner with business leaders, analytics teams, engineering, architecture, risk, compliance, and operations to define AI use cases and deliver impactful solutions.

Communicate product vision, roadmap, and outcomes to senior leadership.

Leadership:

Mentor Product Managers and cross-functional teams on AI-first product thinking.

Foster a culture of experimentation, customer obsession, and data-driven decision-making.

Key Success Metrics:

Successful launch and adoption of Gen AI products across business functions.

Improvement in productivity and decision-making through AI-driven analytics.

High user engagement and satisfaction with conversational AI experiences.

AI quality metrics, including accuracy, latency, safety, and cost optimisation, meeting defined benchmarks.

Timely delivery of roadmap commitments while maintaining product quality.

Positive stakeholder feedback and measurable business impact from AI initiatives.

Requirements:

10+ years of Product Management experience with at least 2-3 years leading AI or Gen AI products.

Proven experience building enterprise products from concept through production.

Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, AI Agents, and conversational AI.

Experience working with Azure OpenAI, AWS Bedrock, OpenAI APIs, or similar enterprise AI platforms.

Strong understanding of data platforms, APIs, cloud architecture, and analytics ecosystems.

Experience collaborating with Engineering, Data Science, ML Engineering, and Business teams.

Strong analytical thinking with the ability to translate complex business problems into AI-powered product solutions.

Experience working in Agile product development environments.

Excellent communication, stakeholder management, and leadership skills.

Preferred Skills:

Experience with enterprise analytics platforms and Business Intelligence tools such as Power BI or Tableau.

Familiarity with vector databases, embeddings, semantic search, and AI orchestration frameworks.

Exposure to ML lifecycle management, experimentation frameworks, and AI evaluation methodologies.

BFSI or Financial Services experience is preferred.

MBA or equivalent business qualification is an advantage.