Principal Software Engineer - Enterprise AI Platform

Details

NVIDIA is hiring a Principal Engineer to lead the security foundations for autonomous, self-evolving agents across the enterprise. This role focuses on securing agentic AI, sandboxed execution environments, and the security and safety layers required when agents generate and execute code while accessing internal and external data sources. The engineer will partner with Cloud, AI/ML & Generative AI workforce, internal platform teams building sandboxed environments for LLM-generated code execution, and cross-functional stakeholders including Legal, Security, and Agent Identity teams to build a safety and security program for long-running, self-improving autonomous agents.

Responsibilities

• Lead end-to-end technical strategy and execution for securing autonomous agents across the enterprise with a bias for enabling developer velocity.
• Define agent security and safety requirements and translate them into scalable architectures, guardrails, and platform capabilities; extend existing sandbox foundations for LLM-generated code execution to support autonomous, tool-using agents and multi-step workflows.
• Design and implement strong isolation, policy enforcement, and least-privilege access controls for agent runtimes and tool integrations.
• Define and enforce build-time guardrails (policy gates, secure defaults, capability declarations) and run-time guardrails (behavioral boundaries, action allowlists, kill switches) that constrain self-evolving agents.
• Build secure pathways for agents to access internal and external data sources, including secrets handling, data protection, and governance controls.
• Establish comprehensive observability and auditing infrastructure (structured logs, decision traces, drift detection, and security telemetry) to ensure agent actions are traceable, measurable, and operationally safe at scale.
• Design and operate a continuous evaluation framework that benchmarks agent behavior, detects capability drift, and validates that self-improving agents remain within approved safety and security envelopes.
• Build a streamlined, developer-friendly experience to run autonomous agents securely—enabling easy onboarding and day-to-day use across both closed-source and open-source agents (examples noted: Claude Code, Codex, OpenCode, Openclaw/Claws) with consistent guardrails, policies, and controls.
• Drive cross-functional alignment and delivery with Cloud, AI/ML & Generative AI workforce, Legal, Security, Agent Identity, and internal platform teams.
• Monitor emerging agent threats and failure modes (especially risks unique to self-evolving agents) and continuously evolve defenses, standards, and best practices for agent safety and security.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• 15+ years of industry experience building and securing large-scale systems, platforms, or infrastructure.
• Proven ability to lead complex technical initiatives as a senior IC—setting direction, driving alignment, and delivering outcomes.
• Strong understanding of security fundamentals: threat modeling, authentication/authorization, least privilege, secrets management, secure SDLC, and incident response.
• Demonstrated experience with sandboxing/isolation technologies (containers, microVMs, Linux security primitives, policy enforcement, runtime controls).
• Experience designing systems with strong observability and auditability (structured logs, traceability, metrics, security telemetry).
• Familiarity with evaluation and benchmarking approaches for AI/ML systems, including designing tests, measuring behavioral drift, and maintaining safety invariants over time.
• Solid programming and systems skills (examples: Python, Go) and comfort working across stack boundaries when needed.
• Ability to operate effectively in a fast-paced, multifaceted environment, with a bias toward action and delivery.

Ways to stand out

• Experience securing agentic AI systems or LLM applications that use tools, execute code, or take autonomous actions—especially self-evolving agents that modify their own prompts, tools, or workflows.
• Hands-on experience with technologies like Kubernetes, containers, workload isolation, policy engines, and runtime security.
• Familiarity with enterprise developer workflows: CI/CD, artifact integrity, dependency/supply-chain security, and secure build pipelines.
• Experience designing governance frameworks for emerging technologies—risk tiering, guardrails, rollout playbooks, and adoption enablement.
• Background in continuous evaluation pipelines for AI systems, including automated red-teaming, regression testing, or safety benchmarking at scale and a strong intuition for balancing developer productivity with security and compliance.

Compensation and benefits

• Base salary range: 272,000 USD - 431,250 USD (base salary will be determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and NVIDIA benefits (link to benefits provided in the original posting).

Other information

• Applications for this job will be accepted at least until March 29, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and states nondiscrimination on protected characteristics.