Staff Software Engineer, Front-End (AI Engineering)

We're looking for a Staff AI Engineer (Front end) to help design and scale our Agentic AI Platform , the foundation that enables enterprise teams to build, deploy, and manage intelligent AI agents securely and at scale.

As part of a global AI engineering team spanning the US and India, you'll provide technical leadership, write hands-on code, and mentor peers while shaping platform capabilities that empower applied AI use cases across Okta.

Responsibilities:

• Design and develop platform services for AI agents, including orchestration, lifecycle management, observability, and guardrails.
• Collaborate daily with US counterparts to align on architecture, share roadmaps, and ensure global consistency.
• Build scalable APIs, frameworks, and reusable components that enable teams to rapidly create and deploy secure AI agents.
• Contribute to monitoring, evaluation, and governance features that make AI adoption safe, reliable, and enterprise-ready.
• Partner with Applied AI engineers, product managers, and designers to ensure the platform supports real-world use cases.
• Mentor engineers within the India team, raising the bar on technical craftsmanship and platform design.
• Stay current with advances in agentic AI, orchestration frameworks, and enterprise AI infrastructure.

Requirements:

• 8+ years of software engineering experience, with at least 3+ years in AI/ML platforms or intelligent automation.
• 5+ years in modern frontend frameworks (e.g., React, Vue) with the ability to build functional UI components, integrate APIs, and maintain design consistency.
• Knowledge on Python preferred, Java, Node.js, or Go.
• Expertise in AI agent frameworks (LangGraph preferred), orchestration systems, vector databases, RAG pipelines, and monitoring/observability.
• Strong background in distributed systems, APIs, microservices, container orchestration (ECS/EKS), and cloud platforms (AWS/GCP/Azure).
• Experience building secure, enterprise-grade infrastructure for AI or ML workloads.
• Ability to influence architecture decisions, align with a global team, and set technical direction locally.
• Strong communication and collaboration skills to work effectively across time zones and global teams.