Microsoft
Intelligent Optimization Lead, Continuous Improvement
$102K–$208K
United States · On-site · Full-time · Posted Sep 22, 2026
- Experience
- 4+ years with a Master's Degree, or 6+ years with a degree in a listed field; equivalent experience accepted.
- Education
- Master's Degree in Business, Engineering, Operations, Information Systems, or related field; OR a degree in Business, Engineering, Operations, Information Systems or related field; OR equivalent experience.
About the job
Leads continuous improvement across customer AI engagements, using measurement and structured improvement cycles to sustain adoption, optimize agents and workflows, and transfer the operating rhythm to customer teams.
What you'll do
- Establish and run a permanent continuous improvement framework, including facilitation, standard work, ownership, and execution cadences.
- Use adoption and operational signals to prioritize workflow, prompt, enablement, and agent improvements; rework or retire low-value assets.
- Transfer improvement practices, cadences, and tools to customer teams so they can continue independently.
What they ask for
- Master's degree in Business, Engineering, Operations, Information Systems, or related field and 4+ years of relevant experience; OR a degree in one of those fields and 6+ years of relevant experience; OR equivalent experience.
- Relevant experience must be in continuous improvement, operational excellence, process improvement, or transformation delivery.
Nice to have
- Hands-on kaizen, Lean, or comparable methodology experience; Lean, Six Sigma (Green/Black Belt), or equivalent certification.
- Experience improving production AI or automation, including agent or prompt performance; familiarity with Microsoft Copilot adoption and the Copilot Dashboard in Viva Insights.
Pay
USD $101,800 - $193,800 per year (base pay); USD $126,100 - $207,600 per year (base pay)
Tools
Copilot Dashboard, Viva Insights, Work IQ
AI focus
Improves AI adoption and value over time by tuning prompts and agent configurations, monitoring agent drift and performance, and reallocating investment toward high-value agents.
Model-written summary · the original posting is authoritative