Technical Project & Product Manager
Pentas Vision · West Region ·
- Work mode
- Onsite
- Category
- Product
PMBD | Technology Strategy | Singapore
Department : PMBD (Project Management & Business Development)
Function : Technology Strategy
Location : Singapore
Reports to : Section Manager, PMBD
Job family : Solution Manager
Position OverviewThe Technical Project & Product Manager is responsible for transforming technology assets and ambiguous business opportunities into well-defined projects, validated product concepts, and decision-ready recommendations.
This role serves as the primary owner of selected cross-divisional initiatives spanning Automotive, Mobile, New Business Development, and other strategic domains within Sony Semiconductor Solutions. The role also supports the commercialization of emerging technology assets, particularly in Physical AI, robotics, and advanced sensing, by driving use-case development, product planning, feasibility validation, proof-of-concepts (PoCs), and business evaluation.
Success in this role requires strong project leadership, product thinking, technical fluency, and the ability to align stakeholders across headquarters, R&D teams, business units, customers, and external partners.
ROLE MISSION Turn technology assets and ambiguous business needs into well-defined projects, validated product concepts, and decision-ready evidence.Key Responsibilities
1. Project Leadership
Lead assigned cross-divisional projects from initiation through delivery.
Define project objectives, sponsors, scope, milestones, dependencies, risks, decisions, success measures, and acceptance criteria.
Drive stakeholder alignment, track execution, and ensure that delivery outcomes meet agreed business expectations.
2. Product Definition & Requirements Management
Translate ambiguous business needs, customer requests, and market opportunities into structured use cases and requirements.
Define functional requirements, priorities, assumptions, constraints, and measurable acceptance criteria.
Distinguish the underlying requirement from a proposed solution and clarify needs before they become engineering commitments.
3. Technology Assessment & Opportunity Development
Work with R&D and architecture owners to understand algorithms, sensing capabilities, SDKs, interfaces, system constraints, and integration dependencies.
Map available technology assets to customer workflows, market evidence, and potential solution opportunities.
Identify gaps, trade-offs, and evidence required to determine technical feasibility.
4. Physical AI & New Business Productization
Define target users, workflows, value propositions, minimum viable scope, and product or solution hypotheses for Physical AI and robotics opportunities.
Assess technical feasibility, business viability, and potential commercialization pathways.
Develop recommendations for pilots, products, partnerships, investments, or stop decisions.
5. PoC & Validation Management
Define the validation question, evidence required, technical and business success criteria, accountable owners, and decision gates.
Coordinate PoC planning and execution across technical and business stakeholders.
Recommend continuation, pivot, or termination based on documented evidence.
6. Risk & Decision Management
Identify material risks, issues, and dependencies early enough for stakeholders to act.
Escalate in a decision-ready format: issue, evidence, options, recommendation, owner, and impact.
Maintain clear decision records and close action loops.
7. Cross-Functional Collaboration
Coordinate R&D, Product, Architecture, Business Development, headquarters divisions, customers, and partners without relying on line authority.
Build alignment across geographically distributed and multicultural teams.
Communicate technical and commercial trade-offs clearly to both working teams and executives.
8. Organizational Knowledge & Reusable Assets
Create and maintain reusable requirement patterns, project practices, technical asset maps, decision records, risk patterns, and validation evidence.
Capture lessons learned so that each new engagement starts from a stronger foundation.
Promote reuse of knowledge across vertical projects and Physical AI opportunities.
Required
Bachelor's degree in Engineering, Computer Science, or a related technical discipline, or equivalent practical experience.
Minimum three years of experience working in a multicultural team is preferred.
Demonstrated ownership of a complex technical project, product workstream, solution deployment, or customer implementation from definition through outcome.
Experience coordinating interdependent technologies such as hardware, software, sensors, embedded systems, AI/ML, SDKs, platforms, or system integration.
Ability to write clear use cases, functional requirements, priorities, assumptions, constraints, and acceptance criteria.
Technical fluency sufficient to discuss interfaces, architecture, dependencies, feasibility, KPIs, verification, trade-offs, and integration risks with engineering owners.
Product judgment to connect customer workflow, value proposition, technology capability, and validation evidence into a coherent product or solution direction.
Strong cross-functional ownership and influence across engineering, product, business, customers, partners, and geographically distributed headquarters teams.
Excellent written and verbal English, including concise executive status and decision communication.
Preferred
Experience in automotive, robotics, industrial sensing, computer vision, semiconductors, embodied intelligence, or Physical AI.
Experience defining PoCs, product qualification, system validation, SDK adoption, partner integration, or commercialization pathways.
Background in product management, solutions engineering, customer engineering, or technical business development.
Ability to perform light technical analysis, test planning, data review, SDK exploration, or rapid feasibility checks.
Japanese and/or Mandarin language capability for regional customer, partner, and SSS-group coordination.
Project Execution
Priority projects have explicit sponsors, intended outcomes, technical owners, milestones, next decisions, and acceptance criteria.
Material risks and dependencies are visible early enough for stakeholders to act.
Customer and divisional needs are clarified before becoming engineering commitments.
Product & Opportunity Development
Physical AI and new-business concepts progress to a clear pilot, PoC, product, partnership, investment, or stop decision.
Product recommendations are supported by customer, market, and technical evidence.
Technology feasibility is concluded through evidence and accountable technical dialogue rather than assumption.
Decision Quality
Critical decisions are presented with clear evidence, options, recommendations, ownership, and impact.
Stakeholders can make informed decisions efficiently and understand the relevant trade-offs.
Issues are escalated early and action loops are closed.
Organizational Impact
Assets created in one engagement reduce ambiguity or accelerate work in another.
Reusable frameworks, technical asset maps, validation evidence, and lessons learned are adopted across projects.
Stakeholders trust the role holder’s judgment, representation of trade-offs, written communication, and follow-through.
You will be measured by outcomes advanced, decisions improved, risks surfaced, product options validated, and learning reused, not by meeting volume or reporting activity.
Mindset We Value
Ownership. Treat the outcome as your responsibility and close loops even when authority is distributed.
Evidence over assumption. Find the right customer, market, or technical evidence before making commitments.
Clarity under ambiguity. Turn broad requests into a structured problem, decision path, and accountable plan.
Commercial curiosity. Ask how a technology asset could solve a valuable problem and become a product, partnership, or future option.
Reusable thinking. Leave behind assets and learning that strengthen the next project.