AI Product Manager

We’re Hiring | AI Product Manager – Purple Fabric (Intellect)
Job Title: AI Product Manager
Business Unit: Purple Fabric (PF)
Experience: 6–12 Years
Job Location: Chennai, India
Employment Type: Full-time
About Purple Fabric
Purple Fabric is Intellect's enterprise AI and decisioning platform, designed to help organizations build, orchestrate, govern, and scale AI-powered solutions. The platform enables enterprises to leverage Agentic AI, intelligent automation, and data-driven decisioning to solve complex business challenges while ensuring security, governance, explainability, and scalability.
We are looking for an experienced and outcome-driven AI Product Manager to drive product strategy, roadmap, and execution for Purple Fabric. The ideal candidate will combine strong product management fundamentals with a practical understanding of Generative AI, Agentic AI, LLMs, and enterprise AI applications.
Role Overview
As an AI Product Manager, you will own the product lifecycle from discovery and conceptualization to development, launch, and continuous improvement. You will work closely with engineering, AI/ML, design, architecture, presales, and business teams to translate customer needs into scalable AI product capabilities.
The role requires someone who can demonstrate 0→1 product creation and 1→N product scaling, with the ability to define product direction, prioritize high-impact use cases, and deliver measurable business outcomes.
Key Responsibilities
1. Product Strategy and Roadmap
Define and execute the product vision, strategy, and roadmap aligned with Purple Fabric's business objectives.
Identify enterprise AI opportunities, customer pain points, and market trends to shape product priorities.
Translate business strategy into product requirements, release plans, and measurable outcomes.
Drive product development from concept to launch and scale successful capabilities across customer segments.
2. AI and Agentic AI Product Management
Define product capabilities involving Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and agent orchestration.
Identify and prioritize enterprise use cases for AI-powered workflows, intelligent automation, and decision support.
Work with AI/ML and engineering teams to define agent workflows, tool integrations, context management, and human-in-the-loop controls.
Understand AI evaluation methods, including accuracy, relevance, groundedness, latency, cost, and reliability.
Drive product requirements for responsible AI, guardrails, explainability, observability, and governance.
3. Product Discovery and Customer Engagement
Engage with customers, business stakeholders, and internal teams to understand business problems and validate product opportunities.
Conduct market research, customer interviews, competitive analysis, and product discovery exercises.
Convert customer feedback and business requirements into product features, user stories, and acceptance criteria.
Validate product-market fit through prototypes, proof of concepts, pilots, and customer feedback.
4. Product Execution and Cross-Functional Collaboration
Collaborate with engineering, AI/ML, UX/UI, architecture, QA, and delivery teams to drive product development.
Own and prioritize the product backlog based on customer value, business impact, technical feasibility, and strategic alignment.
Define product requirements documents (PRDs), user stories, acceptance criteria, and release objectives.
Manage dependencies, resolve prioritization conflicts, and ensure timely delivery of product milestones.
Participate in sprint planning, reviews, product demos, and release planning.
5. Enterprise AI Platform and Governance
Drive capabilities that support enterprise-grade AI adoption, including security, access control, data privacy, governance, and auditability.
Work with architecture and engineering teams to address scalability, integration, deployment flexibility, and performance.
Understand enterprise AI infrastructure, model lifecycle management, model selection, and cost optimization.
Ensure AI product capabilities align with enterprise requirements for reliability, compliance, and responsible deployment.
6. Product Launch, Adoption, and Growth
Define go-to-market plans, product positioning, value propositions, and launch strategies in collaboration with Sales, Marketing, and Presales teams.
Develop product documentation, enablement material, demonstrations, and customer-facing collateral.
Monitor adoption, customer satisfaction, feature usage, and business impact.
Use product analytics and customer feedback to improve usability, adoption, and product performance.
Support product expansion across industries, use cases, and customer segments.
Required Skills and Qualifications
6–12 years of overall experience, with substantial experience in product management for technology products.
Demonstrated experience owning and delivering AI-powered products or enterprise software products with meaningful AI capabilities.
Strong understanding of Generative AI, LLMs, RAG, AI agents, and Agentic AI architectures.
Proven experience in building products from 0→1 and scaling products from 1→N.
Experience translating customer and business requirements into product strategy, roadmaps, PRDs, and prioritized backlogs.
Understanding of AI evaluation, model performance, hallucination mitigation, guardrails, and responsible AI practices.
Strong analytical, problem-solving, prioritization, and decision-making skills.
Excellent communication, stakeholder management, and cross-functional collaboration skills.
Ability to work effectively with technical teams while translating complex AI concepts into business value.
Preferred Qualifications
Experience with enterprise AI platforms, AI orchestration frameworks, agentic workflows, or AI-powered SaaS products.
Exposure to cloud-native platforms, APIs, microservices, enterprise integrations, and data platforms.
Experience in financial services, banking, payments, lending, fraud detection, or other regulated industries.
Familiarity with product analytics, experimentation, Agile methodologies, and product-led growth.
Experience supporting enterprise customer demonstrations, proof of concepts, and go-to-market initiatives.
Success Metrics
Successful delivery of product roadmap milestones and releases.
Adoption and usage of AI product capabilities by enterprise customers.
Measurable improvements in customer outcomes and product-market fit.
Quality and reliability of AI-powered features based on defined evaluation metrics.
Reduction in time to launch, implementation effort, and cost of AI deployment.
Customer satisfaction, product retention, and contribution to business growth.
Ideal Candidate Profile
We are looking for a product leader who combines strong product ownership with genuine AI depth. The ideal candidate should be able to explain the architecture and practical limitations of AI-powered products, make informed product trade-offs, and demonstrate how they have taken an AI product from initial concept to production and subsequently scaled it.
Candidates whose experience is limited to generic SaaS product management, AI feature awareness, or workflow automation without meaningful AI product ownership may not be suitable for this role.

Work arrangement
No