Senior Manager - Digital Product Management

American Express•Sunnyvale, CA

About The Position

As Senior Product Manager for Developer AI Tools, you will own the portfolio of AI coding tools and agents that American Express engineers use to write, review, test, and ship code, including agentic tools such as Claude Code, Codex, and Devin. You will decide which tools to offer, for which work and to whom, and ensure each tool is secure, well integrated with engineering platforms, widely adopted, and delivering measurable value. You will report to the Director of Product Management, Agentic SDLC, and work daily with platform engineering, developer experience, Cyber Security, Technology Risk, and vendor partners. The role is suited to a product manager who uses these tools hands-on, can hold credible technical conversations with senior engineers, and cares as much about adoption and outcomes as launches.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.
7+ years of experience in product management, software engineering, or developer experience, including 4+ years as a product manager on developer tools, developer platforms, or internal engineering products.
Regular hands-on use of AI coding tools and agents, such as Claude Code, Codex, Devin, GitHub Copilot, or Cursor, with an informed view of their strengths and limitations.
Working knowledge of how LLM-based agents operate, including context and prompting, tool use and MCP, model selection, evaluation methods, and usage-based pricing cost drivers.
Understanding of agentic risks in software delivery, including prompt injection, excessive permissions, secrets and data leakage, insecure generated code, and code provenance.
Solid grounding in the modern SDLC, including Git and SCM platforms such as GitHub or GitLab, CI/CD, code review, automated testing, and artifact management.
Experience running structured tool evaluations or pilots and turning results into adoption decisions using metrics such as DORA, SPACE, or developer experience surveys.
Experience working with vendors on roadmap, support, and commercial terms.
Strong written and verbal communication, with the ability to influence engineers and senior leaders without direct authority and drive decisions across Security, Risk, and Engineering.
Eligibility to work with American Express in the United States; the company will not pursue visa sponsorship for these positions.

Responsibilities

Own the product strategy and roadmap for developer AI tools, spanning in-IDE assistants, terminal and command-line coding agents, and autonomous or background agents that take on tickets and open pull requests.
Evaluate AI coding tools and models against criteria including task success on company codebases, code quality, security posture, data handling, integration fit, and cost; recommend which tools to adopt, expand, consolidate, or retire.
Lead enterprise rollout of selected tools, from pilot cohorts through general availability, including onboarding, licensing, configuration standards, and support models.
Define how tools connect to the engineering platform, including SSO and identity, repository and internal-context access, MCP servers and other integrations, CI/CD, ticketing, and knowledge sources.
Partner with Cyber Security, Technology Risk, and Model Risk to set guardrails for AI coding tools, such as permissions and sandboxing, secrets and data protections, approved model endpoints, code provenance, and audit logging.
Work with the Agentic SDLC controls and governance team to ensure AI-generated code follows the same review, testing, and release controls as other changes.
Run continuous discovery with engineers and engineering leaders across languages, stacks, and maturity levels; turn findings into a prioritized backlog and clear requirements.
Manage vendor relationships, including roadmap influence, feature requests, escalations, usage reviews, and input into commercial negotiations.
Build enablement that changes behavior, including playbooks, shared prompts and configurations, reusable skills and agent instructions, office hours, and a champion network.
Define and track success metrics, such as active and retained usage, accepted suggestions and merged agent pull requests, lead time and cycle time, change failure rate, developer satisfaction, and cost per seat and per completed task.
Report adoption, value, and risk clearly to the Director and senior engineering leadership, and make the case for where to invest next.