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 lifecycles, including CI/CD/CT.
Curiosity, analytical openness, and willingness to test ideas, learn from evidence, and refine recommendations over time.

AI Engineer – AI Efficiency, Economics

Key skills