ST Engineering Hiring! Full Time Product Manager - DS-EZ in - Ricebowl

About ST Engineering

ST Engineering is a global technology, defence, and engineering group with offices across Asia, Europe, the Middle East, and the U.S., serving customers in more than 100 countries. The Group uses technology and innovation to solve real-world problems and improve lives through its diverse portfolio of businesses across the aerospace, smart city, defence, and public security segments. Headquartered in Singapore, ST Engineering ranks among the largest companies listed on the Singapore Exchange.

Our history spans more than 50 years, and our strategy is underpinned by our core values – Integrity, Value Creation, Courage, Commitment and Compassion. These 5 core values guide every aspect of our business and are embedded in our ST Engineering culture – from the people we hire, to working with each other, to our partners and customers.

Together, We Can Make A Significant Impact

You will lead end-to-end delivery and commercialisation of AI products, from problem discovery and data readiness through model development, launch, adoption and continuous improvement. The portfolio will include AI Software Products, such as speech-to-text and speech intelligence, large language models (LLMs), AI agents for various mission critical use cases.

Be Part of Our Success

• Define the product vision, value proposition, target users and outcome-based roadmap for AI products such as speech-to-text, LLM/VLM-powered applications, AI agent solutions.
• Identify and validate the riskiest assumptions across user desirability, data availability and quality, model feasibility, responsible-AI risks, operational readiness and commercial viability before committing to build.
• Translate user and business needs into product requirements, story maps, user stories and clear acceptance criteria for data, models, APIs, user experiences, guardrails and human-in-the-loop workflows.
• Partner with AI/ML, data, software, platform, cybersecurity, legal and/or domain teams to prioritise the backlog and manage dependencies across experimentation, model integration, deployment and operations.
• Define fit-for-purpose evaluation frameworks and release criteria, including speech recognition accuracy, LLM groundedness and hallucination risk, agent task-completion quality, latency, reliability, safety and cost per transaction.
• Drive productisation from proof of concept to production, covering build-versus-buy decisions, model and vendor selection, deployment approach, API or platform integration, observability, support and lifecycle management.
• Partner with AI/ML, cybersecurity, legal and governance stakeholders to define and operationalise Responsible AI requirements, ensuring privacy, security, content safety, model governance and regulatory considerations are incorporated into product requirements, release criteria and lifecycle management.
• Define go-to-market, pricing or chargeback approach, adoption plans, measurement frameworks and analytics instrumentation; monitor post-launch usage, quality, customer value and unit economics to guide iteration.
• Facilitate discovery workshops, technical-product reviews, demonstrations and stakeholder alignment, while coaching client and junior Product Managers in evidence-based AI product practices.

Qualities We Value

• Experience: 5+ years across the full product lifecycle, with evidence of taking digital or AI-enabled products from discovery and experimentation into production, adoption and measurable outcomes.
• AI product knowledge: Practical understanding of the AI product lifecycle, including data readiness, model evaluation, prompt and retrieval patterns, agent workflows, APIs, cloud or on-premise deployment, monitoring and continuous improvement.
• Product methods: Strong command of Lean Startup, Continuous Discovery, OKRs, JTBD, Impact Mapping, story mapping and outcome-based roadmaps, adapted for the uncertainty and experimentation involved in AI products.
• Governance mindset: Able to balance product velocity with privacy, cybersecurity, responsible AI, model risk and regulatory or customer assurance requirements, particularly for sensitive speech, generative AI and synthetic-media use cases.
• Leadership and consulting: Experience influencing multidisciplinary teams, coaching Product Managers or Product Owners, and communicating trade-offs among customer value, model quality, delivery risk, cost and time to market. Familiarity or prior experience with the Singapore Government ecosystem (SHIP-HATS, Singapore Government Tech Stack and GeBIZ) and/or working in a highly regulated environment for Mission Critical Systems (in Defence, Home Team, Healthcare, Finance etc.) is an advantage.

Soft Skills

• Communication and collaboration: Excellent verbal and written communication skills, with the ability to explain AI product capabilities, limitations, risks and trade-offs clearly to technical and non-technical stakeholders.
• Adaptability and continuous learning: Comfortable working with rapidly evolving AI models, tooling, regulations and incomplete evidence, and able to update product direction as new findings emerge.
• Analytical judgement: Able to interpret user feedback, experiment results, model-evaluation data, operational metrics and commercial signals to make evidence-based product decisions.
• AI Product Leadership and teamwork: A collaborative team member who can align product, engineering, AI/ML, business and governance stakeholders, while guiding less-experienced Product Managers.
• Execution discipline: Resourceful, independent, responsive and conscientious, with strong time management across concurrent discovery, research, engineering and go-to-market priorities.