Software Engineer, Developer Productivity
Rithum
AWSAzureCloudDockerGoogle Cloud PlatformJavaJavaScriptKubernetesPythonTypeScript
AI Enablement Engineer
ButterflyMX
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureGoogle Cloud PlatformSDLC
About the role
- Lead training sessions, workshops, and office hours to upskill developers on AI-assisted development, code generation, and debugging.
- Design and maintain internal playbooks, best practices, and evaluation frameworks for AI use in the SDLC.
- Partner with engineering leaders to shape interview strategies that fairly and effectively evaluate AI-related skills.
- Trial emerging AI-powered IDEs, copilots, and dev tools; synthesize findings; and make recommendations for adoption.
- Manage access to AI services (API keys, usage monitoring, budget tracking) to ensure secure, responsible, and cost-effective usage.
- Benchmark and compare tools for performance, developer experience, and ROI.
- Identify and deliver agentic solutions across the SDLC (e.g., automated code review, test generation, documentation assistants, issue triage).
- Work with platform and DevOps teams to integrate AI tools into CI/CD pipelines where appropriate.
- Collaborate with security and InfoSec to ensure responsible use of AI within the development process.
- Track adoption, developer satisfaction, and measurable improvements in development speed and quality.
- Provide clear reporting to stakeholders on AI’s role in accelerating engineering outcomes.
- Maintain a pulse on the fast-moving AI developer tooling ecosystem.
Requirements
- Strong technical foundation as a software engineer, developer advocate, or similar role.
- Familiarity with modern AI developer tools (e.g., GitHub Copilot, Cursor, Codeium, Tabnine, AWS/GCP/Azure copilots).
- Experience integrating AI into developer workflows or driving tooling adoption within an engineering org.
- Clear, engaging communication skills for running training sessions, presenting tool evaluations, and influencing developer practices.
- Strong organizational skills: you can track API usage, manage budgets, and keep multiple trials and pilots on course.
- Hands-on work with AI frameworks like LangChain, LlamaIndex, or Hugging Face in engineering contexts (preferred).
- Experience with CI/CD automation, DevOps, or developer platform engineering (preferred).
- Knowledge of secure coding practices and AI governance concerns (preferred).
- Previous experience in developer enablement, productivity engineering, or engineering management (preferred).
- Authorization to work in the US
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