IT Automation and AI Engineer

Secure Every Identity, from AI to Human

Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

The Opportunity

As an IT Automation and AI Engineer at Okta, you will be a key contributor to the team building the platforms and services that drive our internal AI transformation. We are moving beyond simple automation to build sophisticated, "agentic" workflows—utilizing LangGraph and Gemini Enterprise to create stateful, reasoning-capable systems that support our global workforce.

This is a hands-on role for a professional engineer who excels at writing production-grade Python and is eager to bridge the gap between AI research and enterprise-scale applications. You will own the implementation of core features, orchestrating complex LLM interactions while ensuring performance, security, and reliability.

What You’ll Be Doing

• Build Agentic Workflows: Develop and maintain stateful multi-agent systems using LangGraph to solve complex, non-linear business tasks.
• Gemini Integration: Implement and optimize LLM interactions using Gemini Enterprise, focusing on prompt engineering, function calling, and structured outputs.
• State & Memory Management: Design and manage agent state, persistence, and "human-in-the-loop" checkpoints to ensure reliable automated decision-making.
• Backend Development: Write high-quality, production-ready Python code to build the APIs and services that power our internal AI ecosystem.
• RAG & Grounding: Work on Retrieval-Augmented Generation (RAG) pipelines to ensure agents have access to accurate, real-time enterprise context.
• Infrastructure & Deployment: Deploy and manage services on GCP using containerized environments (Docker/Kubernetes) and Infrastructure as Code (Terraform).
• Operational Excellence: Promote engineering best practices around testing AI logic, security, and CI/CD to ensure services are production-ready.

What You’ll Bring to the Role

• Professional Python Core: 2–4 years of software engineering experience with a deep command of Python and its asynchronous ecosystem.