AI Enablement Engineer

About the role

We are looking for an AI Enablement Engineer to sit at the center of how our engineering organization works with AI — spanning tooling support, an internal agentic SDLC platform, and product incubation. You will work closely with the AI Enablement Lead, Director of Engineering, and product leadership to translate internal AI workflows into features we ship to customers.

What you will do

• Own the day-to-day configuration and optimization of AI coding and productivity tools;
• Act as the primary point of contact for engineers, triaging and resolving issues like integration failures, model compatibility, or configuration drift;
• Maintain onboarding documentation and runbooks to ensure engineers of all levels can use AI effectively;
• Run enablement sessions and office hours to drive adoption and guide engineers on best practices for AI-assisted development;
• Gather feedback from teams to translate real usage patterns into continuous improvements for workflows and tooling;
• Drive the refinement and expansion of an internal agentic pipeline that connects specification, implementation, testing, and validation into a coherent automated workflow;
• Own the integration layer between AI agents and the development toolchain, including third-party integrations, execution environments, and context injection strategies;
• Advance specification quality by building tooling, templates, and workflows that help engineers write specs that agents can act on reliably;
• Design and run experiments to validate agent configuration decisions and translate findings into platform improvements;
• Evaluate emerging tools and platforms for potential integration into the agentic workflow;
• Serve as the primary internal test bed for AI-powered features and workflows intended to ship to external customers;
• Collaborate with product and engineering leadership to translate internal learnings into product insights and roadmap inputs;
• Prototype AI-assisted developer experiences that can graduate into product features for SaaS customers;
• Maintain a rigorous dogfood culture by using products internally and bringing insights back into the development process.

Must haves

• 5+ years of experience in a software engineering, DevOps, or platform engineering role with any backend language such as PHP, Java, TypeScript, JavaScript, Python, C#, .NET, or Golang;
• 1+ years of hands-on experience with LLM-based tools or agentic workflows in a professional setting;
• Hands-on experience with AI coding assistants such as Claude Code, Windsurf, Amp, or Cursor;
• Comfort working across multiple technologies and a mixed-technical environment;
• Direct experience deploying and supporting AI coding assistants across a large engineering team, including configuration, rollout, and troubleshooting;
• Ability to understand complex engineering problems and design practical, scalable solutions;
• Familiarity with LLM infrastructure concepts including model routing, API proxying, token management, and model versioning;
• Strong written communication skills;
• Comfort working with engineers at varying AI maturity levels;
• Experience working with automated testing toolchains in a CI/CD context;
• Upper-intermediate English level.

Nice to haves

• Familiarity with PHP and/or C# environments;
• Hands-on experience building or operating agentic AI workflows, including multi-step agent pipelines and tool/API integration;
• Experience with spec-driven or structured software specification methodologies;
• Background in SaaS product development;
• Experience in a developer tools, testing tools, or security software company;
• Experience working in distributed teams across multiple time zones.