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Senior Staff Software Engineer - AI Agent Platform

NVIDIANVIDIA·Semiconductors

Compensation

$168,000 - $322,000/year

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Posted

40 days

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About the role

We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the intersection of distributed systems, developer platforms, and agentic AI — building the foundational services that enable teams across the company to develop, deploy, orchestrate, and operate autonomous AI agents at production scale.

What you will be doing:

  • Build and develop platform services that own the full agent lifecycle from registration through deployment, execution, and teardown

  • Architect Kubernetes-based execution environments with pod lifecycle management, namespace isolation, persistent storage, and identity propagation

  • Develop and maintain automated CI/CD pipelines using GitLab CI and ArgoCD, including reusable pipeline templates and deployment blueprints that standardize how agents are built across teams

  • Build framework-agnostic infrastructure supporting multiple agent SDKs (Claude Code, OpenAI Codex, LangGraph), with hands-on experience using harnesses, lifecycle hooks, skills configurability, observability (OTEL), and memory services

  • Build and operate Kafka-based message pipelines and real-time event streaming using Redis PubSub and SSE

  • Develop data ingestion pipelines, access interfaces, and storage layers that power AI agent knowledge and context

  • Implement session management for state persistence, conversation history, and agent recovery across sessions

  • Develop multi-layer auth using OAuth 2.0, JWT validation, token exchange, and gateway integration, and manage secrets lifecycle with Vault (provisioning, rotation, container injection)

  • Partner with security teams on compliance, access controls, and approval workflows for agent operations

What we need to see:

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent experience), with 8+ years in software engineering — ideally in platform engineering, infrastructure, or developer tools

  • Experience building and scaling AI agents in production using frameworks like Claude Code, Codex, or LangGraph

  • Deep Kubernetes expertise including pod orchestration, persistent storage, RBAC, and multi-cluster management

  • Strong Python skills with production API experience using FastAPI, Flask, or similar async frameworks

  • Proven track record designing distributed systems with Kafka, Redis, and MongoDB or PostgreSQL

  • Expertise building and managing robust CI/CD pipelines using GitLab CI and ArgoCD for continuous delivery to Kubernetes

  • Experience designing AI data platform components (ingestion pipelines, vector stores, retrieval APIs, data preprocessing workflows) and building developer-facing platform APIs consumed by multiple engineering teams

  • Solid grasp of auth and identity: OAuth 2.0, JWT, token exchange, and secrets management with Vault

  • History of leading sophisticated technical projects such as migrations or greenfield platform builds, with strong interpersonal skills to drive alignment across teams and write clear design documents

Ways to stand out from the crowd:

  • Experience building or operating AI agent platforms or agentic workflow systems, with hands-on expertise in agent protocols and frameworks like MCP, A2A, LangChain, or LangGraph

  • Hands-on experience with RAG architectures, embedding pipelines, and vector databases (Milvus, Pinecone, or Weaviate)

  • Full-stack skills with React or Vue for building developer portals and dashboards

  • Contributions to open-source infrastructure or platform tooling

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 4, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Skills & Tags

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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • The company invests heavily in AI and deep learning, driving technological advancements.
  • NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • High competition in the semiconductor industry can impact market share.
  • Rapid technological changes require constant adaptation and learning.
  • Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • The company's AI research is at the forefront of deep learning innovation.
  • NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About NVIDIA

NVDA$204.87+2.22%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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