Description
At NVIDIA, we are building the next generation of AI-native software systems. As AI evolves from assistant-based workflows to autonomous systems capable of reasoning, planning, and acting, we are looking for exceptional engineers to help define and build the underlying platforms that power this transformation.
As a Senior Software Engineer, Agentic AI Systems, you will design and develop production-scale AI systems that combine large language models, retrieval, memory, orchestration, evaluation, and tools into intelligent software capable of solving complex real-world problems. This role sits at the intersection of AI, distributed systems, software engineering, and developer productivity.
Responsibilities:
- Design and implement intelligent systems that can reason, plan, and execute complex multi-step workflows.
- Develop architectures that combine LLMs, retrieval systems, memory, tools, and feedback loops.
- Build autonomous and semi-autonomous workflows that improve engineering productivity and operational efficiency.
- Design scalable backend services, APIs, and distributed systems supporting AI-native applications.
- Build orchestration frameworks for multi-agent and tool-based systems.
- Develop evaluation frameworks that measure accuracy, reliability, latency, and task completion.
- Partner with AI researchers, infrastructure teams, product teams, and software engineering organizations.
Requirements:
- BS, MS, or PhD in Computer Science, Computer Engineering, or a related field.
- 5+ years of software engineering experience. Strong proficiency in Python and modern software development practices.
- Experience building scalable distributed systems and cloud-native services. Experience developing AI-enabled applications using LLMs, RAG, agent frameworks, or workflow orchestration systems.
- Proven experience designing, building, and operating large-scale production software systems.
- Strong understanding of distributed systems, scalability, reliability, observability, and performance engineering.
- Demonstrated ability to own services from architecture and implementation through production operations and long-term maintenance.
- Ability to balance rapid innovation with engineering rigor, maintainability, and operational excellence.
Preferred Qualifications:
- Experience building production AI agents or autonomous systems. Experience with reasoning frameworks, planning systems, memory architectures, and tool-use ecosystems.
- Experience with vector databases, retrieval systems, knowledge graphs, or semantic search. Experience with AI evaluation, benchmarking, and observability platforms.
- Built and operated business-critical platforms serving large user bases or high-volume workloads.
- Experience modernizing early-stage prototypes into robust production systems.
- Deep expertise in system architecture, reliability engineering, and technical leadership. Track record of reducing operational complexity while increasing scalability and maintainability.