Senior Software Engineer, Agentic AI Systems

NVIDIA NVIDIA · Semiconductors · Ho Chi Minh City, Vietnam +1

Senior Software Engineer role focused on building production-scale AI systems, specifically agentic AI systems that combine LLMs, retrieval, memory, orchestration, and evaluation for complex real-world problems. The role emphasizes designing and implementing intelligent systems, developing architectures for LLMs and related components, building autonomous workflows, and creating scalable backend services and orchestration frameworks. Strong software engineering fundamentals, distributed systems experience, and operational excellence are critical.

What you'd actually do

  1. Design and implement intelligent systems that can reason, plan, and execute complex multi-step workflows.
  2. Develop architectures that combine LLMs, retrieval systems, memory, tools, and feedback loops.
  3. Build autonomous and semi-autonomous workflows that improve engineering productivity and operational efficiency.
  4. Design scalable backend services, APIs, and distributed systems supporting AI-native applications.
  5. Build orchestration frameworks for multi-agent and tool-based systems.

Skills

Required

  • Python
  • modern software development practices
  • scalable distributed systems
  • cloud-native services
  • AI-enabled applications using LLMs, RAG, agent frameworks, or workflow orchestration systems
  • designing, building, and operating large-scale production software systems
  • distributed systems
  • scalability
  • reliability
  • observability
  • performance engineering
  • own services from architecture and implementation through production operations and long-term maintenance

Nice to have

  • Experience building production AI agents or autonomous systems
  • reasoning frameworks
  • planning systems
  • memory architectures
  • tool-use ecosystems
  • vector databases
  • retrieval systems
  • knowledge graphs
  • semantic search
  • AI evaluation
  • benchmarking
  • observability platforms
  • business-critical platforms serving large user bases or high-volume workloads
  • modernizing early-stage prototypes into robust production systems
  • system architecture
  • reliability engineering
  • technical leadership
  • reducing operational complexity while increasing scalability and maintainability

What the JD emphasized

  • production-scale AI systems
  • autonomous systems
  • reasoning, planning, and acting
  • complex real-world problems
  • production-scale AI systems
  • autonomous and semi-autonomous workflows
  • large-scale production software systems
  • AI agents not as prompts, but as software systems

Other signals

  • building production-scale AI systems
  • autonomous systems capable of reasoning, planning, and acting
  • design and implement intelligent systems that can reason, plan, and execute complex multi-step workflows