· Own the capability as a product. Backlog,
roadmap and the contracts offered to consuming teams. Decide what gets built,
declined and deferred — and defend it in writing.
· Own assistant behavior. When the
assistant acts automatically versus suggests versus asks; how confidence is
gated and when it should abstain; how it opens a conversation the user did not
start; what it does on cold start, when uncertain, and when wrong. Work with
UX/CX on the interaction contract across voice and screen — turn-taking,
interruption, error recovery, and how much the assistant may reveal that it
remembers.
· Own the quality bar. Grounding,
tool-calling boundaries, guardrails, and the evaluation set — what “good”
means, who labels it, how regression is caught before release. Set and defend
thresholds on the components you depend on: recognition accuracy under real
noise, latency, intent accuracy, recommendation precision. Know why a strong
offline metric can still be a bad outcome.
· Turn requirements into acceptance. Convert
business objectives and use cases into system requirements and acceptance
criteria with explicit numeric thresholds — accuracy, latency, coverage,
false-trigger and abstain rate, cold-start behavior. Own the Definition of Done
and maintain traceability from stakeholder requirement through architecture to
system test, in line with the program’s process framework (Automotive SPICE,
SYS.1–SYS.5), including readiness for formal assessment.
· Run delivery. Sprint planning, release
plan, dependency register, critical path and risk log, defect triage, QC entry
and exit criteria, hand-over at acceptance milestones. Raise slippage early
enough that it is still a decision rather than an announcement.
· Close cross-team contracts. Data
contracts with the platform team (schema, freshness, frequency, volume budget),
service contracts with the cloud team, deployment contracts with the on-device
team, acceptance contracts with product experience and validation. Convert
“we’ll look into it” into an owner, a scope and a date.
· Own the product side of privacy. Personalization
runs on personal behavioral data & at times on voice: what & why is
collected, retention, consent, deletion, and the boundary of what may be
inferred or surfaced
RequirementsEducation & experience
· Bachelor’s degree or higher in Computer Science,
Software Engineering, Data Science, Electronics/Telecommunications, HCI or a
related discipline.
· 5–8 years total professional experience,
with at least 3 years as a Product Owner / Product Manager / Technical
Program Manager on a product that shipped to production. Earlier time as an
engineer, data scientist, UX designer or QA counts toward the total.
· Mandatory — depth in at least one of: conversational AI / virtual assistant products; LLM or agent systems (RAG, tool
use, evaluation, guardrails); speech and audio (ASR, TTS, wake word, audio
front-end — noise, echo, speaker separation); personalization or recommendation
systems; platform or API products consumed by other engineering teams. Depth in
one is what we look for; breadth is a bonus, not an expectation.
· Automotive, EV, embedded and IoT experience
is a plus.
You will spend your week in rooms full of architects and ML
engineers, without a translator. You must be able to:
· Read, critique and write a service
contract, a data schema and a sequence diagram.
· Explain the lifecycle of the AI system you have
worked on, and where quality is lost along it.
· Reason quantitatively about an end-to-end
latency budget, and about what belongs on-device versus in the cloud.
· Pull and sanity-check your own numbers — working
SQL, comfort with a BI or notebook tool.
· Hold a position in an architecture review:
disagree with a technical reason, and change your mind when given a better one.
Coding is not
required. Being unable to follow the discussion is disqualifying.
· Ownership of a backlog from problem statement to
release, with acceptance criteria a QA engineer can execute without asking
you a question.
· Advanced Jira and Confluence; sprint mechanics,
dependency and risk management, release planning, defect triage.
· A track record of negotiating scope — you
have cut or deferred a committed feature, secured it in writing, and made it
hold.
· Experience driving external teams, who do not
report to you, to dated commitments.
· Certifications (CSM/PSPO, PMI-ACP, PMP, SAFe)
are welcome but do not substitute for this evidence.
· Writes short, precise, unambiguous documents. A one-page decision note beats a forty-slide deck.
· Influences without authority; stays factual
under pressure — names gaps, not individuals.
· Holds a position against senior stakeholders
when the data supports it, and concedes cleanly when it does not.
· Vietnamese native or fluent; English professional working proficiency — reading technical specifications, writing
status and design notes, presenting to international partners.
Skills Required
- Bachelor's degree or higher in Computer Science, Software Engineering, Data Science, Electronics/Telecommunications, HCI, or a related discipline
- 5–8 years of total professional experience
- At least 3 years as a Product Owner, Product Manager, or Technical Program Manager on a product shipped to production
- Depth in at least one area: conversational AI or virtual assistants; LLM or agent systems; speech and audio; personalization or recommendation systems; or platform/API products consumed by engineering teams
- Ability to read, critique, and write service contracts, data schemas, and sequence diagrams
- Ability to explain an AI system lifecycle and identify where quality is lost
- Quantitative reasoning about end-to-end latency budgets and on-device versus cloud architecture
- Working SQL and comfort with BI or notebook tools
- Ability to participate in architecture reviews and evaluate technical tradeoffs
- Backlog ownership from problem statement through release, with executable acceptance criteria
- Advanced Jira and Confluence proficiency, including sprint mechanics, dependency and risk management, release planning, and defect triage
- Track record negotiating scope and securing dated commitments from teams without direct reporting authority
- Vietnamese native or fluent proficiency
- Professional working proficiency in English
- Automotive, EV, embedded, or IoT experience
- CSM, PSPO, PMI-ACP, PMP, or SAFe certification
What We Do
VinFast is a Vietnamese automotive manufacturer focused on electric mobility. The company designs and produces smart electric vehicles, including cars, SUVs, e-buses and e-scooters, combining advanced technology with highly automated manufacturing. Its mission is to make sustainable transportation accessible worldwide and accelerate the transition to an all-electric future through innovative, environmentally friendly products, charging solutions, warranties, and customer services.








