Senior Software Engineer, Agentic Engineering

Join the new Agentic Engineering team, within the Deep Learning Framework Group,  build the agentic workflows that automate code generation, testing, and tuning across NVIDIA's frameworks, compilers, and developer tooling. The team is a force multiplier for the engineers behind that stack. This greenfield opportunity offers foundational technical influence within a high-autonomy team inside Deep Learning Frameworks. We partner directly with early-adopter teams to translate complex requirements into durable, scalable infrastructure that other teams can adopt.

The work sits at a genuinely rare intersection: modern AI applied to the craft of engineering itself, inside a company whose hardware powers the AI revolution.

What you'll be doing:

Our initial customers are NVIDIA's early-adopter engineering teams. You will develop a deep, shared understanding with them, identifying the friction points where agentic workflows would have the highest impact. Requirements will evolve as these teams integrate agents into production, so you will iterate with them on proof points to validate or revise your plans together. As an applied ML expert, you will use technical judgment to distinguish durable architectural opportunities from "tech du jour" hype.

The work spans several areas. You might agent-ify compiler infrastructure to enable autonomous agents to make high-dimensional optimizations, with closed-loop validation on real hardware. Multi-agent orchestration is core, anything from LLM-native tooling to custom work with frameworks like Lang Chain/Lang Graph, driving autonomous loops that apply changes, measure results, ratchet forward and repeat. We integrate these systems into git-native workflows and CI pipelines so agents can build, test, and iterate against real GPUs.

Familiarity with NVIDIA's latest GPUs comes with the territory, since the work targets the teams that support them. We contribute to cross-org collaborative group sharing reusable agentic methodology, helping the broader organization adopt what works.

What We Need To See:

MS in Computer Science, Engineering, or equivalent experience
12+ years of experience.

Strong Python development skills

Working knowledge of GPUs or other highly data-parallel systems

Demonstrated projects or work experience using and supporting AI systems

Track record of shipping complex projects with minimal direction, including raising challenges or syncing at the right moments

Experience building tools or systems shaped by direct partnership with internal customer or user teams

Examples of leading technical work through changing requirements and revising direction when evidence demands it Experience in one or more of the following areas:

Multi-agent orchestration frameworks (e.g., Lang Chain, Lang Graph) or LLM-based workflow automation

Compiler infrastructure, intermediate representations, or program transformation

Autonomous search or optimization over high-dimensional parameter spaces

Hardware-aware performance optimization for deep learning workloads

Code generation systems or domain-specific languages (DSLs)
Ways to stand out from the crowd:

Passion for following the evolution of ML hardware and staying up to date on emerging kernel programming techniques

Experience building evaluation or testing harnesses, especially for ML systems or multi-agent workflows

Track record of building internal tools or frameworks that force-multiply engineering teams

Demonstrated ability to thrive in ambiguous, self-directed environments while remaining humble: communicating with clarity, actively listening, and finding ground truth

An allergic reaction to "solutions in search of problems"Your base salary will be determined based on your location, experience, and the pay of employees in…