AI Adoption Engineer: Scale Enterprise AI Platforms
Amgen SA
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Job summary
Amgen is seeking an AI Adoption Engineer to act as the technical catalyst for enterprise adoption of AI tools and AI-enabled development workflows in Washington, DC area. You will drive adoption of ChatGPT, Copilot, Codex, and other AI tools while building reusable AI solutions and automation.
You will conduct technical workshops, mentor teams on AI best practices, and collaborate with Product and Engineering to scale AI adoption, evaluate emerging AI technologies, and measure productivity
Qualifications
- Bachelor's or Master's degree in CS, AI, ML, or related field.
- 8–12 years of software engineering, AI, or machine learning experience.
- Strong Python programming and REST API development experience.
- Hands-on experience with LLMs, ChatGPT, GitHub Copilot, Codex, Claude, or similar AI tools.
- Experience building AI-powered applications and workflow automation.
- Knowledge of prompt engineering and AI enablement practices.
- Excellent communication, technical mentoring, and stakeholder management skills
Responsibilities
- Drive adoption of ChatGPT, GitHub Copilot, Codex, and other AI tools while building reusable AI solutions, agents, and workflow automations.
- Conduct technical workshops, mentor teams on AI best practices, and collaborate with Product and Engineering to scale AI adoption.
- Support multiple cross functional teams on use case execution with AI tools (codex and ChatGPT work)
- Evaluate emerging AI technologies, develop proof of concepts, and measure AI adoption and productivity improvements.
Skills
Education
Tools
Job description
Amgen is seeking an AI Adoption Engineer to act as the technical catalyst for enterprise adoption of AI tools and AI-enabled development workflows in Washington, DC area. You will drive adoption of ChatGPT, Copilot, Codex, and other AI tools while building reusable AI solutions and automation.
You will conduct technical workshops, mentor teams on AI best practices, and collaborate with Product and Engineering to scale AI adoption, evaluate emerging AI technologies, and measure productivity
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