Required

Bachelors degree in Business, Marketing, Engineering, or a related field.

6+ years of proven experience in product management or related roles.

1+ years of building AI based intelligent products

1+ year’s experience in using GenAI tools to perform product management tasks like conduct idea research, shaping, synthesis, roadmaps, requirements, prototyping, testing

Limited immigration sponsorship may be available

Ability to travel 0-20%, on average, based on the work you do and the clients and industries/sectors you serve

Ability to work in your local office at a minimum of 3 days per week

Candidates must be located within a commutable distance to one of the select location available for this role

Preferred

Experience being accountable for value and viability results for an empowered product team.

Experience in modern product craft of delivering the right thing, in the right way, at the right time.

Experience in modern product management craft and domain (tools, methods, and practices).

Experience with lean solutions and rapid, inexpensive experimentation to emerge the right thing, in the right way, at the right time.

Accountability for value, viability and P&L; objectives for a product.

Quick to reach expert-level knowledge within the product domain being served.

Analytical Skills: Ability to analyze data and derive actionable insights.

Problem-Solving: Innovative and experimental approach to solving complex problems.

Leadership: Ability to lead and inspire cross-functional teams, fostering collaboration and collective movement toward product goals.

Customer-Centricity: Deep understanding of customer needs and engagement patterns, driving teams to deliver solutions that customers love and that work for the business.

Strategic Thinking: Ability to develop and execute a strategic vision for the product, aligning it with broader business objectives.

AI Agentic Fluency: Comfortable orchestrating multiple AI agents across the concept-to-cash flow (research, insight, prototyping, specification, coding, and compliance), with guardrails at each hand-off—assumptions, confidence levels, and links to sources of truth.

AI Realism and Eval Fluency: Understands the difference between deterministic logic and probabilistic generation; designs guardrails for hallucination, bias,



and drift; uses evaluation harnesses before launch and monitors drift after, with a kill-switch mentality—and knows when not to use AI.

For Manager Level

Required Qualifications

Education: Bachelor’s degree in business, Marketing, Engineering, or a related field.

10+ years of proven experience in lean product management or related roles.

3+ years enterprise scale experience across multiple business areas.

1+ years of building AI based intelligent products

1+ year’s experience in using GenAI tools to perform product management tasks like conduct idea research, shaping, synthesis, roadmaps, requirements, prototyping, testing

Key Responsibilities

1 )Product Accountability

Responsible and accountable for the product's value and viability showcasing a measurable Return on Investments (ROI)

Drive strategy-aligned solutions to achieve product value objectives.

Formulate and achieve Key Performance Indicators (KPIs) for identified problems to solve.

Measure KPIs and analyze outcomes to inform future strategies.

Leverage AI to harvest outcome evidence early and often, lowering total cost of ownership (TCO).

1. Vision and Strategy Co-create, own, and evangelize the product vision, strategy, and roadmap, using AI to deepen domain knowledge and simulate future scenarios to chart pathways others have not yet seen.

Align product objectives with the product line and business goals.

Co-create in collaboration with business stakeholders, engineering, experience, and delivery.

Use AI to expedite research, gather evidence, bolster domain knowledge, and craft and cutting-edge visions backed by compelling strategic rationale.

2. Market and User Engagement Conduct user research and competitive analysis, using AI agents to synthesize research at speed—accelerating the data crunching, ensuring the human connection.

Engage the team with users and stakeholders through continuous research and direct interactions.





Collaborate and guide the team toward solutions that address priority user and business needs.

Apply analytical skills to analyze data and derive actionable insights, shifting from waiting on analysis to working on insights.

Adopt innovative and experimental approaches to solving complex problems, including AI-built, disposable prototypes that validate solutions quickly and retire bad ideas just as fast.

3. Collaboration and Teamwork Work side-by-side with cross-functional (business, engineering, experience, and delivery) team members to achieve KPI outcomes.

Promote a product operating model that emphasizes outcomes over output (minimize overproduction while maximizing value).

Build empowered teams and product communities who exhibit collective product ownership and level-up their outcome potential through AI and agentic tools.

4. Continuous Improvement Promote and drive rapid, emergent, and ongoing learning and adaptation to meet objectives.

Drive innovation and improvement of the process to drive out waste and accelerate value achievement, using AI as a force-multiplier to offload the repetitive, speed up the sluggish, and automate the mundane.

Remove obstacles for the team and ensure smooth flow of continuous value achievement.

Spread knowledge and best practices within the product vertical community.

5. Applied AI Ways of Working Amplify innovation: use AI to rapidly deepen domain knowledge, surface untapped market and user potential, and simulate future scenarios—charting new pathways for the business.

Amplify learning: use AI agents to synthesize research and validate ideas before they enter the backlog—compressing lead time by accelerating the data crunching, ensuring the human connection.

Amplify focus: act as Editor-in-Chief—using AI to rigorously test assumptions and retire ideas that do not genuinely serve the user’s workflow in a way that works for the business.

Amplify experimentation: use AI to build early, functional, disposable prototypes that validate the architecture and the solution, playing a key role in the Agentic Secure Software Development Life Cycle that paves a clear path to productionize early and often.

Preferred Qualifications Preferred Education: An MBA or related advanced degree is preferred.

📌 Generative AI Product manager (Bengaluru)
🏢 Anlage Infotech
📍 Bengaluru