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AI Engineer (Education & Research)

Trường Đại học VinUni · Hà Nội
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Loại hình
Toàn thời gian
Hình thức
Tại văn phòng
Cấp bậc
Nhân viên
Ngành nghề
Kỹ thuật / Cơ khí
Mức lương
Thương lượng
Địa điểm
Hà Nội, Hà Nội, Hà Nội

So sánh mức lương? Mức lương ngành Kỹ thuật / Cơ khí →

Tổng quan

  • AI Product Development

Yêu cầu

  • Translate business needs and use cases in learning, teaching and research — adaptive and personalized learning, AI-assisted teaching, AI support for academic research — into AI features with clear scope and success criteria.
  • Deliver production AI features and backend services integrated with the LMS, single sign-on and University systems; define data collection requirements from the outset.
  • Use AI agents and tools across the development lifecycle — research and assessment of emerging technologies, task decomposition, coding, test generation, code review, documentation and monitoring — and continuously improve the team's development practices.
  • Adoption & Collaboration
  • Continue supporting features after release until users have adopted them; translate usability issues, unusual use cases and unmet needs observed in real use into specific, prioritized recommendations for the Product Owner.
  • Work with the Product Owner, the AI Product Manager, faculty, researchers and Vingroup's platform and security teams throughout the product lifecycle.
  • AI Systems Engineering
  • LLM, Retrieval & Agents
  • Build production LLM applications with prompt and context management, structured outputs, hybrid retrieval over course and academic content, and agent workflows with tool use, memory and multi-step orchestration (e.g. LangChain, LangGraph, LlamaIndex).
  • Improve reliability and cost efficiency by implementing guardrails, fallback mechanisms, human-review steps where AI output requires a person's decision, model routing, caching and per-user usage controls.
  • Data for AI
  • Build the data foundations behind the products: ingestion and chunking of course and academic documents, embeddings and vector stores, access control on learner and research data.
  • Prepare datasets for fine-tuning or domain adaptation where justified.
  • Quality, Evaluation & LLMOps
  • AI Evaluation
  • Build and maintain automated evaluations for every release, assessing accuracy, groundedness, hallucinations, safety, guardrail adherence, latency, cost and user value using curated test sets, LLM-as-judge and samples of real usage.
  • Build validated reference datasets for AI evaluation with subject-matter experts coordinated by the Product Owner. Validate prompt and model changes against agreed evaluation criteria before adoption.
  • LLMOps & Operations
  • Implement tracing and observability for AI features (e.g. Langfuse); version prompts, models and evaluation sets; run evaluations in CI so regressions are caught before release.
  • Monitor production behavior, investigate incidents and quality regressions, and optimize services for quality, latency, reliability and cost.
  • Architecture, Security & Standards
  • Architecture & Standards
  • Contribute to technology roadmaps, technical standards and solution architecture; present and justify technical designs during Vingroup's architecture reviews.
  • Generalize solutions into reusable components and patterns; make technical trade-offs explicit and explain them to non-technical colleagues.
  • AI Application Security & Compliance
  • Build AI-specific safeguards into the application: defenses against prompt injection and data leakage, protection of personal data in prompts and logs, and pedagogical guardrails such as tutors that guide rather than give answers.
  • Deliver within Vingroup's development, security and AI-risk processes; maintain source code, technical documentation and user guides to the team's standards.
  • Applied Research & Mentoring
  • Research to Product
  • Stay current with advances in LLMs, agents and evaluation; proactively test new tools and research methods against the current system and adopt those that improve results.
  • Contribute to controlled experiments on new AI capabilities and document results that can inform product decisions or be reported or published.
  • Mentoring & Knowledge Sharing
  • Mentor and train fresh graduates and junior engineers through hands-on technical guidance, code reviews, pair programming and regular feedback.
  • Contribute documentation, demonstrations and internal sessions that help colleagues adopt what you build.

Quyền lợi

  • Healthcare Insurance
  • Training
  • Laptop
  • The salary and benefits are competitive and commensurate with qualifications and experience.
Chăm sóc sức khỏeĐào tạoLaptop / Thiết bị

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