Principal Engineer - AI Systems

Autodesk Autodesk · Enterprise · Bangalore, India

Principal Engineer role at Autodesk focused on designing, building, and scaling complex software systems with a strong emphasis on AI capabilities, specifically intelligent agents and automation systems. The role involves architecting platforms, leading development, and integrating modern AI/ML frameworks and agent-based systems into production.

What you'd actually do

  1. Design and architect scalable, reliable, and high-performance software systems and platforms
  2. Lead end-to-end development of complex applications, from concept to deployment
  3. Define system architecture, design patterns, and best practices across teams
  4. Write clean, maintainable, and efficient code across multiple layers (backend, APIs, distributed systems)
  5. Evaluate and integrate modern technologies, including AI/ML frameworks and agent-based systems

Skills

Required

  • 10+ years of professional software development experience
  • Strong expertise in system design, distributed systems, and scalable architectures
  • Proficiency in one or more languages such as Python, Java, Go, or C++
  • Experience with cloud platforms (AWS, Azure, or GCP)
  • Solid understanding of APIs, microservices, and event-driven architecture
  • Hands-on experience with databases (SQL and NoSQL)
  • Strong problem-solving and debugging skills
  • Experience or strong interest in building AI-powered systems
  • Strong ownership and accountability
  • Ability to think in systems and long-term architecture
  • Curiosity and adaptability toward emerging technologies (especially AI)
  • Clear communicator who can bridge technical and business discussions
  • Familiarity with LLMs, prompt engineering, and AI agent frameworks (e.g., LangChain, AutoGen, CrewAI, etc.)
  • Ability to design autonomous or semi-autonomous agents that interact with tools, APIs, and workflows
  • Understanding of vector databases, embeddings, and retrieval systems (RAG)
  • Experience integrating AI into production systems

Nice to have

  • Experience in platform engineering or building developer tools
  • Knowledge of MLOps, model deployment, and monitoring
  • Exposure to Kubernetes, Docker, and CI/CD pipelines
  • Prior experience in technical leadership or architect roles
  • Experience building multi-agent systems
  • Contributions to open-source projects
  • Experience with real-time systems or high-throughput platforms

What the JD emphasized

  • 10+ years of professional software development experience
  • Experience integrating AI into production systems
  • Ability to design autonomous or semi-autonomous agents that interact with tools, APIs, and workflows

Other signals

  • design and develop AI agents for automation, decision-making, and workflow orchestration
  • Ability to design autonomous or semi-autonomous agents that interact with tools, APIs, and workflows
  • Familiarity with LLMs, prompt engineering, and AI agent frameworks (e.g., LangChain, AutoGen, CrewAI, etc.)