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Metro location and broad AI enablement skills attract moderate competition despite specialized adoption focus.
Enterprise AI adoption experience and regulated-industry familiarity moderately limit cross-industry transferability.
Explicit 8–12 years requirement plus mandatory LLM, Python, and API skills enforces strict shortlisting.
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Accelerate enterprise adoption of AI technologies such as ChatGPT, Codex, AI agents, and AI-enabled workflows by driving usage and building reusable AI solutions and automations.
Conduct technical workshops, mentor teams on AI best practices, and collaborate with Product and Engineering to scale AI adoption across multiple cross-functional teams.
Evaluate emerging AI technologies, develop proofs of concept, and measure AI adoption and productivity improvements combining hands-on engineering with technical consulting and enablement.
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related field.
8 to 12 years of software engineering, AI, or machine learning experience.
Strong Python programming and REST API development skills.
Hands-on experience with large language models (LLMs) and AI tools such as ChatGPT, GitHub Copilot, Codex, or similar.
Experienced in building AI-powered applications and workflow automation with a focus on prompt engineering and AI enablement.
Capable of delivering technical workshops and mentoring, indicating strong communication and stakeholder management skills.
Familiarity with AI adoption in regulated industries like biotechnology, pharmaceuticals, or healthcare is a plus.