Product Manager

About the role

You sit at the intersection of enterprise customers, our consulting and delivery teams, and our AI infrastructure platform. Your job is to identify the problems worth solving, turn what we learn in client engagements into clear product priorities, and help the team ship capabilities that work in real enterprise environments. This is a hands-on product role in an early-stage company. You will work closely with the founding team, engineers and client-facing colleagues. You will need to move comfortably between customer conversations, product decisions and delivery details.

Key responsibilities

• Own product discovery. Speak with users and enterprise stakeholders, understand their workflows and pain points, and distinguish recurring product needs from one-off client requirements.

• Set priorities and the roadmap. Translate customer evidence, technical constraints and business goals into a practical roadmap. Make trade-offs explicit and explain what we build now, later or not at all.

• Define what good looks like. Write clear product requirements, user stories and acceptance criteria. Align the team on scope, user experience, success measures and release readiness.

• Partner with engineering. Work with engineers on AI workflows, integrations, model access, governance and platform capabilities. Unblock decisions and keep delivery focused on outcomes.

• Bring products to market. Coordinate pilots, launches, user onboarding and feedback loops with delivery and GTM colleagues. Turn early adoption into improvements and repeatable offerings.

• Measure and improve. Track usage, reliability, customer value and product adoption. Use evidence from live deployments to guide the next iteration.

Requirements

• 1–3 years of product experience. Experience in product management, technical product ownership or building software products end to end; ideally in B2B SaaS, enterprise software, AI or developer platforms.

• Strong product judgement. Able to frame ambiguous problems, conduct discovery, prioritise competing requests and make defensible trade-offs with limited resources.

• Technical fluency. Comfortable discussing APIs, data flows, integrations and the basics of LLM applications, including retrieval, agents and evaluation.

• Delivery ownership. Experience working with engineering and design teams to turn requirements into shipped features, with clear acceptance criteria and follow-through.

• Clear communication. Full professional proficiency in English, written and spoken. Able to explain product decisions to technical teams, enterprise customers and business stakeholders.

• Comfort with ambiguity. Self-directed, organised and willing to test assumptions, change course and do the practical work needed in a small team.

About us

Praxis Intelligence Pte. Ltd. is a Singapore-based company that takes enterprise AI from strategy to production. Through our consulting and deployment practice, NextAI+ Praxis, we work with enterprises from use-case discovery through solution design, system build and go-live, and we stay through the stage where most AI programmes stall: integration with real data, real systems and real people. Current engagements span maritime, e-commerce, semiconductors and electronics, and traditional energy and manufacturing. We are not a pure consultancy. The practice is supported by our own AI infrastructure layer, an enterprise platform for governed model access, routing and cost attribution across providers and clouds, together with internal build tools that take us from a client interview to a working system in short order.