About the Role
Masan Group's AI team builds and operates AI solutions across our retail, consumer, and F&B ecosystem (WinCommerce, Masan Consumer, Phúc Long, and more). Our flagship platform is a multi-agent AI system in production, currently operating on text and expanding into voice and vision in the next phase. The team is established and growing — the work remains fast-moving: new problems, new technologies, and new solution domains arrive with every project cycle.
We are looking for an AI Engineering Lead to own project delivery end-to-end: leading the engineering team, driving technical investigation into new problem domains, and shipping AI products from concept to production. This is a builder's role with fast project cycles and constant exposure to new problems, not a maintainer's role on a static platform.
What You Will Do
- Own project delivery: translate project scope agreed with business units into technical plans, milestones, and team assignments; drive execution from kickoff to production.
- Lead a team of 5–7 AI engineers: task breakdown, technical review, mentoring, hiring input, and performance feedback.
- Drive technical direction on our agentic AI platform: architecture decisions for multi-agent orchestration, tool use, memory, evaluation, and reliability in production.
- Lead technology investigation for new problem domains — rapidly prototype, assess feasibility, and make build/buy/adapt recommendations for emerging AI capabilities (voice agents, vision-language models, etc.).
- Stay hands-on: write code, review designs, and unblock the team on the hardest technical problems. This is a player-coach role.
- Work across data foundations: partner with data teams on pipelines and infrastructure that feed AI systems.
Must-Have
- 7+ years in software/AI engineering, with 2+ years building LLM-based or agentic AI systems (multi-agent orchestration, tool-calling agents, RAG, agent evaluation) — production experience, not only prototypes.
- Proven technical leadership: has led a team or project workstream of 4+ engineers; comfortable owning delivery under ambiguity.
- Strong software engineering fundamentals (Python, system design, API design, deployment of ML/LLM services).
- Ability to move fast under ambiguity: scoping new problem domains, cutting through unknowns, shipping iteratively.
- Strong communication skills: able to represent the AI team with business and senior stakeholders and translate between technical and business language.
Strong Plus
- Data engineering background (pipelines, streaming, data platforms — Spark, Kafka, Airflow, or equivalents).
- Hands-on experience in speech/voice AI (ASR, TTS, speech-to-speech, voice agents) and/or computer vision (VLMs, detection/OCR, video understanding).
- Experience deploying AI in retail, consumer, e-commerce, or operations-heavy domains.
- Track record of taking a new AI capability from research/POC to production at scale.
