Software Architect, AI Systems and Platform

Okta•San Francisco, CA

About The Position

Okta is hiring two hands-on software architects for the team building Digital Workers, a suite of autonomous agents for identity operations and security. The team works directly with Okta’s co-founder and CEO and is developing a product intended for Okta’s customers, combining startup-style ownership and pace with the resources of a public company. One architect will focus on agent execution, harnesses, and evaluations; the other will focus on backend services, integrations, data, and platform reliability. Both will write critical production code, resolve cross-team decisions, and work with engineers through production rollout. The role defines shared contracts and service boundaries across model reasoning, agent harnesses, durable workflows, and authorization-enforcing services. Architects will assess and select an agent harness, design model-provider integrations, establish reference services, shape transactional and analytics data architecture, and connect Product, Applied AI, and Platform teams through practical APIs and clear ownership. The role also involves guiding technical leads, reviewing recovery and security approaches, and supporting production rollout and customer expansion. The technology stack includes Python, FastAPI, React, TypeScript, AWS Amplify, Step Functions, Amazon Bedrock AgentCore, Lambda, SQS, EventBridge, API Gateway, RDS PostgreSQL, pgvector, S3, KMS, Secrets Manager, CloudWatch, and CloudTrail. OpenAI and Anthropic API integrations are being added; an agent harness and a dedicated ClickHouse or BigQuery analytics layer are planned, and the architects will help choose and implement them. The position is based on the listed San Francisco Bay Area salary range, though actual base pay depends on skills, qualifications, experience, and work location. Okta also offers equity where applicable, a bonus, and benefits under applicable plans and policies. Okta describes an immersive, in-person onboarding experience and a global community spanning more than 20 offices.

Requirements

Record of leading architecture and delivery across multiple engineering teams.
Recent production code personally implemented.
Deep knowledge of distributed services, API design, data consistency, cloud security, and production operations.
Experience simplifying systems while improving reliability, security, or delivery speed.
Ability to explain design tradeoffs, guide senior engineers, and remain accountable through implementation.
Depth in at least one of the AI systems architect or platform architect focus areas, plus ability to work across the full product.

Nice To Haves

Experience with Claude Agent SDK, OpenAI Codex SDK, Strands Agents, LangChain Deep Agents, LangGraph, or a comparable custom runtime.
Enterprise identity or security products experience.
Experience with OAuth, OIDC, SAML, SCIM, or complex customer integrations.
Experience with ClickHouse, BigQuery, agent evaluations, post-training systems, or open-source infrastructure.
Experience building a new product within a larger enterprise while keeping technical decisions reversible.

Responsibilities

Define and implement shared contracts for tasks, events, permissions, approvals, evidence, and usage.
Establish clear boundaries between model reasoning, agent harnesses, durable workflows, and services that enforce authorization.
Evaluate and select an agent harness using representative identity tasks, failure tests, and operational evidence.
Keep model providers and harness components replaceable.
Design integrations with OpenAI and Anthropic APIs, considering data boundaries, latency, cost, version changes, and measured release quality.
Build reference services for tenant isolation, scoped tool execution, idempotency, long approval waits, and verified results.
Define transactional and analytics data architecture, keeping PostgreSQL application state separate from the planned ClickHouse or BigQuery analytics layer.
Connect Product, Applied AI, and Platform engineers through clear ownership and practical APIs.
Resolve dependencies that slow delivery.
Write critical implementations, review recovery and security, and guide technical leads through production rollout and customer expansion.
For the AI systems architect focus, build and evaluate agent harnesses, context management, model integrations, and quality controls.
For the platform architect focus, lead backend, connector, security, data, and workflow architecture.