Join Infosys Strategic Technology Group (STG):

The innovation engine within the CTO organization, where engineers build next-generation data platforms, AI-first architectures, intelligent products, and large-scale digital ecosystems. STG provides opportunities to work on cutting-edge technologies, collaborate with distinguished technologists, and solve complex engineering challenges for global enterprises.

We are seeking a visionary Principal Product Manager to define and execute the strategy, roadmap, and business outcomes for next-generation AI and Generative AI products.

AI Product Vision & Strategy:

- Define and communicate a compelling vision and long-term roadmap for AI, GenAI, and intelligent platform offerings.

- Identify market opportunities and customer pain points where AI can generate measurable business value.

- Develop product strategies that align business objectives, customer outcomes, and technology investments.

- Continuously evaluate emerging AI technologies and determine their applicability to product portfolios.

Product Roadmap & Prioritization:

- Own product planning and prioritization across multiple AI initiatives and platforms.

- Make data-driven trade-off decisions amidst technical uncertainty, evolving business needs, and resource constraints.

- Balance innovation, customer impact, scalability, and commercial viability when prioritizing investments.

- Ensure focus remains on solving customer problems rather than implementing AI for its own sake.

AI Product Discovery & Experimentation:

- Translate ambiguous AI capabilities into clear product requirements, user stories, acceptance criteria, and measurable outcomes.

- Lead rapid experimentation through MVPs, prototypes, proofs of concept, A/B testing, and evaluation frameworks.

- Define and execute experimentation strategies to validate business hypotheses and product-market fit.

- Accelerate learning cycles by quickly identifying successful use cases and scaling proven solutions.

Product Execution & Delivery:

- Collaborate with Engineering, Data Science, Design, Architecture, and Platform teams to deliver AI-powered products.

- Drive end-to-end product lifecycle management from ideation through launch and scale.

- Remove delivery roadblocks and ensure alignment across cross-functional teams.

- Ensure products meet enterprise-grade requirements for security, scalability, reliability, and performance.

AI Platform & Model Governance:

- Partner with AI engineering teams to evaluate model performance, latency, cost, accuracy, and reliability.

- Define product requirements related to model selection, fine-tuning, orchestration, and AI workflows.

- Drive responsible AI implementation, including fairness, transparency, explainability, privacy, and compliance considerations.

- Establish governance frameworks for AI risk management and ethical AI adoption.

Metrics & Outcome Ownership:

- Own business outcomes and product success metrics rather than feature delivery alone.

- Define KPIs including adoption, engagement, retention, customer satisfaction, revenue impact, and operational efficiency.

- Monitor product performance and continuously optimize based on insights and customer feedback.

- Establish AI-specific evaluation metrics covering accuracy, hallucination rates, response quality, latency, and cost efficiency.

Commercialization & Go-to-Market:

- Develop and execute go-to-market strategies for AI-powered products and platforms.

- Partner with Sales, Marketing, Customer Success, and Business Leaders to drive adoption and revenue growth.

- Build pricing, packaging, positioning, and customer value propositions for AI offerings.

- Support customer engagements, executive briefings, analyst interactions, and strategic product presentations.

Stakeholder Leadership:

- Influence senior executives and stakeholders across technology, business, operations, sales, and customer organizations.

- Act as the central point of alignment between business priorities and product execution.

- Communicate product vision, roadmap progress, risks, and opportunities to leadership teams.

- Mentor Product Managers and help build enterprise-scale product management capabilities.

Required Qualifications:

- Bachelor's or Master's degree in Computer Science, Engineering, Business, Data Science, or related discipline.

- 15+ years of product management experience with proven ownership of large-scale enterprise products.

- Experience delivering AI, Machine Learning, GenAI, Conversational AI, Agentic AI, or Intelligent Automation products.

- Strong understanding of modern AI ecosystems, LLMs, prompt engineering, RAG, AI agents, orchestration frameworks, and model evaluation techniques.

- Demonstrated success in product strategy, roadmap management, and commercialization.

- Experience driving product decisions based on data, experimentation, and customer insights.

- Exceptional stakeholder management, communication, and executive presentation skills.

- Strong analytical mindset with the ability to balance customer value, technical feasibility, and business outcomes.

Preferred Qualifications:

- Experience with OpenAI, Azure AI, Anthropic, Gemini, AWS Bedrock, LangChain, Semantic Kernel, CrewAI, AutoGen, or equivalent AI platforms.

- Knowledge of Responsible AI, AI governance, security, privacy, and compliance frameworks.

- MBA or advanced degree in Business, Technology, Data Science, or Artificial Intelligence.

- Experience launching enterprise SaaS, platform, cloud, or data products.

- Background in Banking, Financial Services, Healthcare, Retail, Manufacturing, or Telecom domains is highly desirable.