Role Overview

AI is rapidly changing how software is designed, built, tested, reviewed, deployed, and operated — and the industry playbook is being rewritten monthly. Okta's Developer Productivity and AI Enablement Engineering teams own building and operating the capabilities that make our engineers fast across the inner and outer development loops. This role is the product counterpart, embedded full-time with that organization, that makes those investments compound by uncovering and prioritizing frictions, bringing the outside in, driving standardize-vs-federate decisions, spreading what works across teams, funding and clearing the path for the best tools, and proving the value.

We are looking for a Senior Product Manager to own developer productivity as a product across Okta's development lifecycle — AI-native and traditional tooling alike. You will start bottom-up: interviewing engineers, managers, tech leads, and architects; mapping current inner- and outer-loop tooling and the frictions; and baselining dev-cycle metrics. From there, you will own the roadmap with engineering leadership; benchmark how the best engineering organizations build with AI; define tooling requirements and/or run the tooling evaluations engineering needs in a landscape that changes monthly; find the teams inside Okta getting outsized results and turn their patterns into playbooks; lead build, buy, integrate, and standardize decisions, including the vision for reducing implementation diversity across Okta and Auth0; clear the security, legal, procurement, and budget paths that slow adoption; and own the measurement that connects investment to engineering outcomes — evidence engineering leaders can take into any room.

This is a highly technical internal platform role that creates value for Okta through a cross-team, cross-industry, cross-functional layer that turns individual wins into organizational capability.

What You'll Do

• Product Strategy & Discovery: Own the vision, PRDs, and prioritized backlog for Okta's internal developer productivity and AI tooling. Treat engineers as your customers: start with deep, bottom-up discovery (dozens of engineer, EM, tech lead, and architect interviews), baseline dev-cycle metrics, and secure tooling budgets with rigorous, ROI-driven business cases.
• Ecosystem Validation (Build vs. Buy): Drive definitive "adopt, build, or pass" decisions. Run hands-on, structured evaluations of inner- and outer-loop tooling — from coding agents and MCPs to build, CI/CD, and code review systems — against strict security and TCO criteria to ensure internal investments amplify vendor capabilities.
• Hands-On Execution: Embed full-time with Developer Productivity Engineering and own the roadmap jointly with its engineering leads. Define MVP scopes, manage sprints, and incrementally ship workflows. You own the strategy and requirements (the what and why); Engineering owns the technical execution (the how).
• Adoption & Outcomes: Own org-wide adoption, clearing security, legal, and privacy hurdles along the way. Measure success by connecting tool usage directly to hard engineering outcomes (cycle time, quality, toil reduction).
• Standardization & Lighthouses: Coordinate the vision for reducing implementation diversity across Okta and Auth0 engineering. Study high-performing teams to see who is getting exceptional results, and convert those patterns into scalable playbooks that shift the broader org from passive AI use to agentic workflows.

What We're Looking For

• 5+ years of product management experience with developer platforms, developer tools, cloud infrastructure, or AI products.
• Experience owning internal or platform products where users have alternatives — adoption driven through product quality rather than mandate.
• Strong understanding of modern software development workflows — source control, IDEs, CI/CD, testing, code review, observability, production operations — across the inner and outer loops of development.
• Hands-on, current fluency with AI-assisted software development — coding agents, context management, MCP, evaluation frameworks — and informed views on where these tools create leverage and where they introduce risk.
• Demonstrated ability to design and run technology evaluations and controlled experiments, and to define measurement systems for developer productivity with judgment about their failure modes.
• Ability to engage credibly in technical and architectural discussions with senior engineers while maintaining clear boundaries between product outcomes and engineering implementation.
• Strong cross-functional leadership and the ability to influence senior stakeholders across engineering, security, architecture, and finance without direct authority.
• Excellent written communication in a docs-first culture; you can produce solid action plans from incomplete, conflicting, or ambiguous inputs.

Preferred Qualifications

• Experience deploying or scaling developer tools across a large, multi-org engineering organization — including consolidating divergent stacks and the change management that comes with it.
• Hands-on familiarity with developer AI tools, harnesses, APIs, MCPs, and agent orchestration frameworks.
• Familiarity with developer productivity research (DORA, SPACE, DX Core 4) and its failure modes.
• Experience establishing governance, evaluation frameworks, or spend management for rapidly evolving, consumption-priced technologies.

Why This Role Matters

AI-assisted development is becoming both one of the largest levers on engineering velocity and one of the largest new variable costs in R&D. The playbook changes monthly, and the organizations that win are the ones that learn fastest from the outside, spread what works internally, and measure honestly. That learning-and-leverage layer doesn't build itself — engineering teams optimizing locally, however well, still leave organizational value uncaptured and accumulate divergent implementations that slow everyone down.

This role exists to capture it: dedicated product leadership that brings engineering the external intelligence, funded tooling, cleared paths, shared patterns, and defensible evidence to build with AI faster than any single team could alone — while deepening Okta's firsthand credibility as the company that secures the AI-powered enterprise for its customers.

**Must attend in person orientation in person the first Tuesday of employment. 
**Must go into the local office 2 days a week.
**Must work North American hours. 

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