Staff Software Engineer (Applied Artificial Intelligence)

• The team that built Jeeva AI is building Digital Workers, a new suite of autonomous agents for identity operations and security inside Okta
• The team works directly with Todd McKinnon, Okta’s co-founder and CEO, with the opportunity to bring this product to Okta’s 20,000+ customers
• You will help shape the product with the ownership and pace of a startup and the resources of a public company
• You will build the harnesses and evaluations that make these workers reliable
• They investigate risk, use tools, wait for approvals and complete tasks across enterprise systems
• Bring depth in agent execution or model quality and help turn it into working software customers can trust
• Build the agent harness for planning, tool use, memory, context compaction, interruption and recovery during long-running work
• Integrate OpenAI and Anthropic model APIs. Select models using measured quality, latency and cost, with clear failure handling
• Evaluate existing harnesses and build only the missing pieces. Keep the harness connected to AWS workflow execution and approval state
• Keep authorization and sensitive writes behind application policy checks. Require evidence of the resulting state before marking work complete
• Build evaluation datasets and replay tests for valid findings, access decisions, app setup and AI agent onboarding
• Measure false positives, missed risks, unsafe actions, completion rate and cost. Turn production failures into regression tests
• Test prompt injection, stale evidence, conflicting instructions and unsafe tool use. Protect tenant boundaries in retrieval and memory
• Improve prompts, retrieval, tools and model routing. Evaluate fine-tuning or other post-training methods when results justify them and data use is approved
• Staff: Lead a domain such as harnesses, evaluations or model quality across workers and implement its critical components

Benefits

• Work from home opportunities
• Health + Wellness
• Financial Benefits
• Pay + Incentives
• Time Off
• Everyday Living
• Resources

• Production builder: You have shipped AI software and know what changes when real users depend on it
• Strong owner: You follow an improvement through code, evaluation, release and customer use
• Careful evaluator: You investigate failures and use evidence to judge quality
• Hands-on experience building agent workflows or evaluation systems for tool-using LLM applications. For harness work, relevant experience includes Claude Agent SDK, OpenAI Codex SDK, Strands Agents, LangChain Deep Agents, LangGraph or a custom implementation
• Experience integrating model APIs, structured outputs and asynchronous services. Experience with OpenAI or Anthropic is especially relevant
• Strong Python engineering skills and experience shipping an LLM application that uses tools
• Depth in agent execution or evaluation systems, with working code and failure analysis you can explain
• Our core stack is Python FastAPI, AWS Step Functions, Amazon Bedrock AgentCore, PostgreSQL on Amazon RDS and pgvector. OpenAI and Anthropic model APIs are part of the integration plan
• We plan to add an agent harness and a dedicated analytics layer using ClickHouse or BigQuery. The harness choice is open. Experience with equivalent tools also counts
• Ability to distinguish a plausible model response from a supported finding or verified action
• Open-source contributions, agent observability, security evaluations or synthetic evaluation data
• Fine-tuning, preference data, post-training evaluation or model distillation using approved datasets
• Identity and security workflows. Foundation-model research experience is optional