product
Posted 13 hours agoProduct Manager -AI
at Epocare
Bangalore, IndiaHybrid
Responsibilities
- Define the vision and roadmap that drive innovation in AI-driven products. Duties &
- Own how business context is represented.
- Define what a customer's business objects, rules, and data look like in a common, structured way, so every team and agent that reads from the platform gets the same, accurate picture regardless of which underlying ERP a customer runs.
- Own the per-customer context record.
- Own the structured record that carries a customer's context cleanly from one part of the system to another, so nothing gets lost as work moves between different Prism products.
- Own the read and write-back loop.
- Own the connection to the ERP.
- Own how the platform exposes ERP data and business logic to the rest of Prism in a consistent way, so other teams build against one clean interface instead of many inconsistent ones.
- Own the catalog of what's built on the platform.
- Own the system that keeps track of which agents, workflows, and tools exist, what they're allowed to touch, and who's using them, so the platform stays legible as more gets built on it.
- Create hands on working prototypes of product concepts in addition to documentation and design.
Requirements
- Overview Every AI agent in Prism needs two things to do real work: an accurate, shared picture of how a customer's business fits together, and a safe way to read from and write back to it.
- You will work with the teams building specific AI products and workflows to make sure they get what they need from the platform, and with the engineers building the platform itself to decide what gets prioritized next.
- Our product organization is in the middle of a deliberate move to a platform-first, AI-enabled delivery model: building shared capabilities that many teams can build on, broadening how roles work together, and removing the silos and handoffs that slow good teams down.
- Real understanding of the end customer whose business data and context flow through the platform, and of the engineering and product teams deciding whether to build on it or work around it.
- Working Backwards: Demonstrates mastery of customer empathy, working backwards from customer pain points to validate the customer problems, ideal customer profiles, and value propositions. ‘Founder Mode’ Mindset: Demonstrates an entrepreneurial spirit by taking full ownership, embracing creative problem-solving, and relentlessly challenging the status quo to drive innovation and continuous improvement.
- Prototyping Pro: Quickly generates prototypes to get early feedback from internal stakeholders and customers.
- Strategic Direction & Prioritization: Lead the orchestration of strategic direction and set priorities for our AI applications and functionalities.
- Stay current on how other companies are approaching knowledge graphs, data platforms, and grounding for AI agents, and fold what's useful into the roadmap so the platform keeps improving instead of other teams quietly building duplicate versions of the same thing.
- Strong product management fundamentals.
- Proven ability to validate customer needs, prioritize ruthlessly, and build a roadmap for a complex product, ideally one that other teams build on top of rather than a single customer-facing feature.
- Working understanding of how knowledge graphs, ontologies, and common data models are typically designed, sufficient to make real product trade-offs with the engineers building the platform rather than just relaying their recommendations.
- Applied AI knowledge.
- Strong working knowledge of AI agents, how they retrieve and ground their reasoning in real data, and how to evaluate whether they're working correctly, enough to make real architecture and trade-off decisions, not just sponsor them.
- Understanding of governance and trust.
- Understanding of how access controls, scoping, and audit trails over business data translate into customer trust, since that trust is the platform's core value. Analytical fluency.
- Familiarity with modern software delivery.
- Familiarity with modern, AI-assisted software delivery and cloud/SaaS platforms.
- Previous ERP experience is a plus. Required
- experience with data platforms, knowledge graphs, ontologies, or applied AI/agent products, with real technical depth rather than purely commercial exposure.
- Education: Bachelor’s degree in Computer Science, Engineering, Business, or a related field (or equivalent experience).
- Advanced degrees are a plus. Additional
- experience with a knowledge graph, ontology, or master/common data model initiative is a strong plus. Hands-on AI experience. Practical
- experience with prompt engineering, retrieval-based AI systems, evaluation methods, and agent orchestration, ideally including using AI coding tools to prototype directly.
- Working proficiency in a language such as Python or C#, enough to read the system's code, prototype against it, and work credibly with engineers.
- Familiarity with GraphQL and REST API design, data pipeline concepts, and how modern AI systems connect to external tools and data.
- Machine learning exposure.
- Exposure to frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus.
- Join 5,000 talented professionals in creating a world of better business through data, AI, and cognitive ERP.
- From software engineers who command the latest AI technology to business development reps who help us seize new opportunities, the work we do matters.
Experience
- Relevant technical depth: 2+ years of
Benefits
- Responsibilities Own the platform vision and roadmap.
- Ability to drive alignment across peer leads in architecture, engineering, and design, and across the product teams that depend on the platform, without having formal authority over any of them, and to explain a clear, credible product vision to each audience.
- And that success really matters, because we’re the essential partners for the world’s most essential businesses—the hardworking companies who make, move, and sell the things the world needs. Competitive Pay &
- Work-Life Balance: Policies built on mutual trust and support, encouraging time off to rest, recharge, and reconnect.
Additional details
- The Prism Platform is that shared foundation, a knowledge layer that describes a customer's business objects and rules, a common way of representing data across different underlying ERP systems, and a structured, per-customer record that carries context cleanly from one part of the system to another.
- You own how that foundation evolves: what gets modeled, how it's exposed to the teams and agents that depend on it, and how it gets more accurate and more useful the more it's used.
- This is a product role at the center of the platform, not on top of it.
- Epicor Epicor is a technology leader in ERP software for manufacturing, distribution, and retail, with deep roots in both enterprise software and startup culture.
- How This Team Works The biggest change versus a traditional PM job is how the work gets done.
- We expect this leader to operate fluently in the model below, and to help the rest of the org adopt it.
- The Prism Platform exists to be depended on by every other part of Prism.
- Ease of adoption for the teams building on it, and the quality of the shared foundation it provides, are the real measures of success, not any single feature.
- Delivery happens in a lean, cross-functional team working closely together against a system with built-in human oversight.
- You are inside that loop as the product decision-maker, not reviewing status from the outside.