Senior Technical Product Manager

Gurugram, Haryana, India

Company Description Firstview Consulting is a professional services firm focused on helping organizations design, build, and scale technology-driven products and solutions. The company partners with clients across industries to solve complex business problems through data-driven insight and modern product practices. Team members collaborate closely with client stakeholders, engineering, and operations to deliver measurable outcomes and long-term value. Firstview Consulting fosters a culture of ownership, continuous learning, and pragmatic innovation, offering opportunities to work on high-impact initiatives and grow into senior leadership roles.

Job Description

An AI Product Manager is a senior individual contributor responsible for ensuring a product’s value and viability within a product line. This role involves leading empowered, cross-functional product teams to solve moderate complexity customer problems that align with high value business needs. The Applied AI Product Manager is accountable for the product’s success, from vision to execution, and collaborates closely with various functions and stakeholders to deliver valuable, viable, usable, and feasible solutions. The Applied AI Product Manager harnesses AI and agentic tools to compress the concept-to-cash learning loop—automating analysis, prototyping, and compliance detail-work so the team can focus on the human judgment AI cannot replace: product sense-making.

Requirements

10-15 years of IT experience, including a strong background in Product Management with ownership of roadmaps and vision
Solid history serving as Product Owner or Product Manager within Agile or SAFE frameworks
Working knowledge of Generative AI, LLMs, RAG, function calling, and multi-agent orchestration
Familiarity with AI Solutions design and AI Content Framework development
Ability to manage AI-related risks
A track record of mapping processes, spotting bottlenecks, and calculating automation ROI
Experience handling non-deterministic software lifecycles where AI behavior isn't always predictable
History of turning large enterprise requirements into staged, incremental deliveries via MVP methods
Skill in bridging technical AI limitations and business context for different audiences

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