AI Enablement Engineer

Responsibilities

• Drive AI adoption and standardization across the engineering organization.
• Enable adoption of AI foundations, standards, frameworks, tooling patterns, and best practices.
• Help standardize the AI Development Lifecycle (AIDLC) by making workflows, expected behaviors, and quality bars clear and easy to adopt.
• Partner with platform, engineering, and operations leaders to integrate AI into default engineering practices.
• Provide practical support through examples, demos, applied workflows, office hours, hack sessions, and team enablement sessions.
• Build feedback loops to identify adoption blockers, tooling gaps, workflow issues, and opportunities to improve AI standards.
• Translate field feedback into updates to playbooks, templates, standards, and training materials.
• Create short recordings, practical reminders, do-and-don’t guides, workflow examples, review checklists, and quick-reference materials.
• Use AI tools to convert source materials into reusable enablement assets and build repeatable prompt, template, and content-generation workflows.
• Define dashboards and metrics for AIDLC adoption, AI tool usage, and productivity impact.
• Create data-backed narratives, leadership updates, success stories, and technical storytelling about AI adoption.
• Support engineering onboarding and role-specific learning related to approved AI tools and workflows.

Requirements

• 5+ years of experience in developer productivity, developer experience, technical enablement, engineering communications, technical program leadership, or a similar technical role.
• Strong understanding of software development lifecycles, code review, testing, developer tooling, platform and reliability concepts, and engineering standards.
• Experience using AI tools such as Claude, ChatGPT, Gamma, Cursor, and related platforms.
• Demonstrated ability to create reusable AI-assisted workflows, prompt libraries, short-form enablement content, templates, and playbooks.
• Ability to translate evolving technical standards into clear, practical guidance for engineers and managers.
• Strong written and verbal communication skills.
• Experience building feedback loops, adoption mechanisms, or learning systems that drive behavioral change at scale.
• Ability to partner across engineering leadership, platform teams, operations, recruiting, and business stakeholders.
• High ownership, sound judgment, attention to detail, and a bias for action in ambiguous environments.

Nice to Have

• Experience in B2B SaaS, platform engineering, identity, fraud, risk, fintech, or other technically complex environments.
• Familiarity with engineering productivity metrics, usage analytics, cost governance, or AI tooling dashboards.
• Experience running office hours, technical communities, guilds, brown bags, or structured enablement programs.
• Familiarity with Notion, Confluence, Slack, Jira, Glean, LearnUpon, Jellyfish, or knowledge automation systems.
• Experience creating executive-ready materials from raw source content.