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Okta is seeking a Staff Software Engineer to join the Agentic Services Engineering Team, focused on building the next generation of AI-integrated tools and infrastructure. The role centers on designing and developing AI-enabled services that allow Okta customers to seamlessly utilize AI agents, with heavy emphasis on the Model Context Protocol (MCP) for connecting AI models to Okta's core capabilities.
Key responsibilities include:
- Design and develop next-generation AI-enabled tools leveraging MCP, enabling customers to integrate AI agents with Okta's platform
- Build, maintain, and contribute to open-source SDKs that empower developers to incorporate Okta into AI-driven applications
- Design, develop, and maintain highly available, scalable, and resilient services with clear low-level designs, robust APIs, and effective data models
- Own end-to-end technical solutions across multiple services or components, ensuring code quality, observability, security, and operational readiness
- Collaborate with product, design, and cross-functional teams to translate business requirements into reusable technical solutions
- Lead code and design reviews, drive engineering best practices, and mentor other engineers
- Diagnose complex production issues, improve reliability and performance through data-driven analysis, and enhance CI/CD pipelines
- Safely integrate and operate AI/ML-enabled solutions, applying AI/ML concepts to real-world products
The role emphasizes raising the bar on engineering practices, serving as a trusted mentor to junior and peer engineers, and acting as a force multiplier across the organization.
Required qualifications:
- 8+ years of backend and distributed systems experience
- Deep expertise in Java, Spring/Spring Boot, and SQL/NoSQL databases
- Strong computer science fundamentals in data structures, algorithms, and advanced system design
- Experience designing and evolving multi-service or domain-level system architectures
- Demonstrated success improving performance, reliability, and scalability of high-traffic systems
- Experience driving engineering excellence initiatives (test automation, CI/CD, security, operational best practices)
- Hands-on experience integrating or operating AI/ML-enabled capabilities in production
- Familiarity with AI-driven developer productivity and observability tools
- Excellent communication and stakeholder management skills
