AI Engineer – AI Efficiency, Economics

Responsibilities

• Assess how engineering teams are currently using AI tools and identify high‑value improvement opportunities.
• Evaluate AI‑assisted workflows using measures such as quality, speed, adoption, and cost efficiency.
• Build lightweight instrumentation, analysis, dashboards, or automation tools to measure AI usage patterns and support optimization experiments.
• Partner with engineering leads and individual contributors across multiple teams to drive adoption and behavior change.
• Present findings, proposals, and results to engineering leadership; create clear, compelling documentation and slide decks.
• Stay current on model capabilities, pricing, workflow patterns, and optimization techniques.

• 5+ years of experience in software engineering, technical strategy, developer productivity, or AI‑enabled workflow optimization.
• Hands‑on experience evaluating or using LLM‑based tools and workflows in technical or enterprise settings.
• Demonstrated ability to drive behavior change, improve operating practices, and influence technical organizations through analysis, recommendations, and collaboration.
• Strong communication and presentation skills.
• Self‑directed and comfortable navigating ambiguity across teams, workflows, and emerging AI practices.
• Experience with LLM evaluation techniques including cost analysis.
• Familiarity with modern software development life cycles, including CI/CD/CT.
• Curiosity, analytical openness, and willingness to test ideas, learn from evidence, and refine recommendations over time.