Senior AI System Architect

About the role

Senior AI System Architect Department: Robotic Solutions Division ABOUT VINDYNAMICS: At VinDynamics, we design safe, affordable, and intelligent humanoid robots to assist in everyday life — robots for everyone. Backed by Vingroup, Vietnam’s leading technology conglomerate, we are on a mission to make advanced robotics accessible, reliable, and beneficial for billions of people worldwide. By combining cutting-edge AI, world-class engineering, and human-centered design, we aim to seamlessly integrate robots into daily life — enhancing safety, productivity, and happiness at home and beyond. Job Summary: We are seeking a Senior AI System Architect to own the end-to-end architectural design of our AI systems powering humanoid robots. You will define how LLM/GenAI capabilities are embedded into robot cognition, how AI workloads are distributed across cloud and edge infrastructure, and how our AI platform supports scalable model development and deployment. This is a pure architecture role — you will set the technical direction, produce authoritative design artifacts, and guide engineering teams without being responsible for day-to-day implementat. REQUIREMENTS Relevant education and experience • Bachelor's degree or higher in Computer Science, AI/ML, Software Engineering, or related fields. Master's or PhD preferred. • 5+ years of experience in software or systems engineering, with at least 2+ years in a dedicated architecture or technical design role. • LLM / GenAI: Deep understanding of large language model architectures, prompt engineering, RAG (Retrieval-Augmented Generation), function calling, multi-modal models, and agentic AI patterns. Hands-on familiarity with leading platforms (OpenAI, Gemini, Claude, open-source LLMs). • ·Cloud / Edge AI: Strong grasp of cloud AI services (AWS, GCP, or Azure AI stacks) and edge inference frameworks (TensorRT, ONNX Runtime, TFLite); ability to design cost-efficient, latency-aware hybrid architectures. • AI Platform & MLOps: Architectural knowledge of ML lifecycle tooling — Kubeflow, MLflow, Weights & Biases, or equivalent; CI/CD for ML; model monitoring and drift detection. • System Design: Proficient in distributed systems design — microservices, event-driven architectures, API gateway patterns, message queues (Kafka, MQTT, or equivalent). • Infrastructure Concepts: Solid understanding of containerization (Docker, Kubernetes), networking fundamentals, and cloud-native design principles. Preferred Qualifications • Experience with real-time AI systems and latency-constrained inference design. • Knowledge of AI safety frameworks, responsible AI governance, and model risk management. • Exposure to multi-agent AI systems or autonomous decision-making architectures. Personality/ Attitude • Senior mindset: Takes ownership of complex problems end-to-end, drives solutions without needing close supervision. • Detail-oriented: Produces clean, well-documented code and integration specs that others can build on. • Collaborative: Works effectively across engineering, product, and customer-facing teams. JOB DESCRIPTION AI Architecture Design • Define the overall AI system architecture for VinDynamics robots — covering inference pipelines, model serving, data flows, and system boundaries. • Architect the integration of LLM and GenAI models into robot cognition layers — including prompt orchestration, context management, multi-modal input handling (vision + language), and real-time response latency management. • Design agentic AI frameworks that allow robots to plan, reason, and act using foundation models in dynamic real-world environments. • Establish architectural standards for AI API contracts between robot runtime, edge nodes, and cloud services. Cloud / Edge AI Infrastructure • Design hybrid cloud-edge AI architectures that balance latency, bandwidth, and compute constraints specific to humanoid robot deployments. • Define infrastructure blueprints for on-device AI inference (edge) and offloaded workloads (cloud) — including failover, fallback, and graceful degradation strategies. • Architect secure, low-latency communication layers between robot fleets and AI backend services. • Define compute and networking requirements in collaboration with infrastructure and DevOps teams. AI Platform & MLOps Architecture • Design the AI platform architecture that supports the full model lifecycle — data ingestion, training, evaluation, versioning, deployment, and monitoring. • Define MLOps workflows and toolchain standards (experiment tracking, model registry, deployment pipelines, A/B testing, observability). • Establish architectural guardrails for responsible AI — including bias evaluation, safety constraints, and audit logging for production AI systems on robots. • Create reusable platform blueprints that accelerate AI feature delivery across product teams. BENEFITS: • Attractive income, competitive and commensurate with individual capabilities. • 13th-month salary, gifts on public holidays and special occasions, and performance-based bonuses. • Meal allowance, annual company trips, health insurance, and exclusive benefits within the Group’s ecosystem. • Clear career development opportunities aligned with the company’s growth, with access to training programs based on capability and job role. • A dynamic and open working environment with diverse cultural and sports activities. Apply for Senior AI System Architect Application submitted successfully