Principal Software Engineer, Agentic AI Applications and Foundations

Nvidia

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $272,000–$431,250 / yr
Posted: 95 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $219k

This role $352k

$125k most similar roles pay here $464k

This role pays more than 99% of similar roles. Most pay $192,050–$246,150 — the shaded band above. At the midpoint, this role pays about $352k versus about $219k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, Agentic AI Applications and Foundations

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Principal Software Engineer — Agentic AI Applications and Foundations joins the Enterprise AI team to harden production systems and architect next-generation agent infrastructure. This role focuses on improving reliability, performance, and observability for desktop, web, and service-based AI products while building resilient frontends, backend APIs, distributed services, and deployment systems. The engineer will develop reusable capabilities such as orchestration services, memory and context services, evaluation frameworks, and policy-aware tool integration to move agentic applications from prototypes to mature software. Key technical requirements include experience with TypeScript, JavaScript, React, Electron, Python, Go, Java, and distributed infrastructure. Candidates must possess expertise in RAG, LLM-powered applications, and agentic workflows while utilizing technologies like Nemotron and NVIDIA AI Blueprints. The role addresses the challenge of creating secure, scalable, and governed systems for enterprise operations and employee productivity.

What does a Software Engineer earn in California?

Median $214000 from 775 postings across 63 companies.

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Skills

Python Go TypeScript JavaScript React Electron LLM RAG CI/CD TensorRT-LLM NeMo Nemotron NVIDIA AI Blueprints SDKs Observability Performance Tuning

What you'll do

Improve reliability, performance, and observability across desktop, web, and service-based AI products.
Design and build resilient frontends, backend APIs, distributed services, and scalable data flows.
Establish robust patterns for testing, CI/CD, monitoring, incident response, and operational excellence.
Build reusable capabilities including orchestration services, memory systems, and evaluation frameworks for multiple agent domains.
Validate and operationalize AI technologies like Nemotron and NVIDIA AI Blueprints in enterprise production settings.
Define the core architecture for how AI agents discover each other and collaborate under enterprise governance.
Codify shared components, documentation, and operational playbooks to create durable infrastructure.
Mentor engineers and lead cross-functional teams to deliver measurable outcomes in employee productivity and operations.

What we're looking for

BS, MS, or equivalent experience in Computer Science or a related field.
15+ years of experience building and operating production software systems.
Experience leading architecture and delivery across the full stack for complex products.
Proficiency in modern application development using technologies like TypeScript, React, Python, Go, Java, and distributed infrastructure.
Expertise in testing strategy, release engineering, observability, performance tuning, and incident response.
Knowledge of AI application patterns including LLM-powered applications, RAG, tool use, and agentic workflows.
Experience building shared services, internal platforms, SDKs, or core infrastructure for multiple teams.
Strong cross-functional leadership skills with the ability to influence across teams while remaining hands-on.

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