Staff Software Engineer, AI/ML

About the role:

Enterprise Technology is building the core AI-native engineering capabilities needed to improve how we design, build, test, and ship software. This role will help apply AI-assisted engineering across Enterprise Technology projects while maintaining strong quality, security, and production-readiness standards.

You will build production software, direct AI coding agents, review AI-generated work, improve delivery practices, and help turn what works into reusable patterns for future Enterprise Technology initiatives.

What You’ll Do:

• Build and ship production software for Enterprise Technology initiatives, including services, APIs, data models, user interfaces, integrations, tests, and operational tooling.
• Direct AI coding agents by writing clear specs, acceptance criteria, implementation plans, and verification steps.
• Review and own AI-generated code, tests, pull requests, and migrations for correctness, security, maintainability, and production readiness.
• Help establish repeatable AI-assisted engineering practices for Enterprise Technology projects.
• Design and implement integration-heavy, data-intensive, and workflow-driven systems for enterprise applications and operational platforms.
• Apply and extend AI-assisted engineering tooling, including coding-agent workflows, repo access patterns, context setup, automated verification, and reusable delivery templates.
• Track practical delivery metrics such as cycle time, quality, rework, test coverage, cost, adoption, and operational health.
• Partner with Product, Security, business stakeholders, and Enterprise Technology teams to deliver secure, maintainable software.
• Improve testing, review, observability, documentation, and operational practices for AI-assisted delivery.

What We’re Looking For:

• 12+ years of experience building and shipping production software as a hands-on engineer, senior IC, technical lead, or Staff-level contributor.
• Strong production experience with Python and/or TypeScript across backend, frontend, data, API, or cloud-native systems.
• Hands-on experience using AI coding agents or tools such as Claude Code, Google Antigravity, Codex, Cursor, or similar systems.
• Strong engineering judgment for reviewing AI-generated code and knowing where human oversight is required.
• Experience building or integrating services, APIs, relational data stores, event-driven systems, and user-facing workflows.
• Familiarity with cloud-native development, preferably GCP, including CI/CD, monitoring, security scanning, and cost-aware engineering.
• Understanding of secure engineering practices, role-based access, SSO, audit logging, and controls for enterprise systems.
• Ability to influence technical decisions, mentor engineers, and raise quality across a significant system or project area.
• Clear written and verbal communication with engineering and non-engineering stakeholders. 

Preferred qualifications:

• Experience with enterprise systems, business applications, workflow platforms, data platforms, or internal tools.
• Experience with media, streaming, content platforms, or complex business domains.
• Experience building developer-facing tools, templates, or internal platforms that help engineers ship software faster and more safely.
• Experience with LLM or agent observability tools such as Datadog, LangSmith, Langfuse, or similar systems.
• Experience with data migration, compliance-sensitive systems, SOX controls, audit-heavy environments, or complex enterprise integrations.