Staff Software Engineer, AI-Core (Federal)

The team is building a scalable Agentic AI platform for agents that run real engineering work, agents that write code, triage incidents, investigate alerts, remediate vulnerabilities, upgrade libraries, patch flaky tests, automate runbooks, and other workloads across Okta's infra. Owning this platform means owning the hard cross cutting problems: agent identity, delegated access, secure isolated execution, orchestration, and governance, at the scale and reliability bar that Infra demands. The work is novel and high ownership, and the candidate should be drawn to problems the industry hasn't solved yet.

• Design and implement backend APIs and services that make up the agentic platform
• Build the agent identity and machine-to-machine authentication system, including credential management and delegated access flows
• Build the agent knowledge base and memory layer so agents retain context within and across sessions
• Build the observability layer for agents: tracing, cost tracking, audit logs, and dashboards that make agent behavior debuggable in production
• Build the governance and safety layer: policy enforcement on tool calls, content filtering, PII protection, and human-in-the-loop approval flows
• Build the orchestration layer that coordinates multi-step agent workflows with state persistence and error recovery
• Collaborate with Product, SRE, Security, Data Platform, Observability and other domain partners to shape what each layer looks like and how it integrates with the broader Okta platform

• 5+ years of software engineering experience building production backend systems.
• 1+ years of exposure to AI/ML or agentic applications, whether through production work, side projects, or hands-on experimentation.
• Strong proficiency in one or more backend languages (Python, TypeScript/Node.js, Go, or similar)
• Hands-on experience designing and operating distributed systems: APIs, microservices, container orchestration, and serverless technologies
• A security-conscious mindset around credential handling, trust boundaries, and what can go wrong at integration points; familiarity with OAuth, OIDC, or other modern auth patterns.
• Comfort operating in ambiguous, fast-moving environments where the problem definition evolves alongside the solution and the right abstractions are still being invented.

Bonus: Exposure to LLM integration, RAG pipelines, MCP, or agent orchestration frameworks like LangChain, LangGraph, or the Claude/OpenAI SDKs.Bonus: Experience with policy-as-code authorization (Cedar, OPA), agent identity patterns, or building developer-facing APIs and SDKs.

• You'll learn fast. The problems this team works on, agentic systems, secure execution at scale, the platform layers that make agents reliable in production, are ones the industry is still figuring out, and you'll be in the room when those answers get written. You'll also have room to shape how you grow, whether that means going deeper on backend systems, leaning into AI/ML, or moving toward technical leadership over time.
• And you'll build things that actually get used. The platform you ship will be the foundation other teams build their agents on, and the work compounds quickly, what you ship this quarter shapes what's possible next quarter. 

The employee must be either a U.S. citizen as defined in 42 U.S. Code § 9102; a natural person who is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or who is a protected individual as defined by 8 U.S.C. 1324b(a)(3); or a U.S. national (i.e. includes citizens and non-citizens born in outlying possessions such as American Samoa and Swains Island), green card holders, refugees, and asylees. Working on a U.S. visa does NOT qualify as a U.S. person.

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