What are the responsibilities and job description for the Senior Software Engineer, Agentic Engineering position at NVIDIA AI?
Job Requisition ID
JR2018162
Job Category
Engineering
Time Type
Full time
Join the new Agentic Engineering team, within the Deep Learning Framework Group, at NVIDIA. We 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 LangChain/LangGraph, 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
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2018162
Job Category
Engineering
Time Type
Full time
Join the new Agentic Engineering team, within the Deep Learning Framework Group, at NVIDIA. We 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 LangChain/LangGraph, 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
- 6 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
- Multi-agent orchestration frameworks (e.g., LangChain, LangGraph) 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)
- 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"
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.