[Hiring] Intelligent Optimization Lead @Microsoft

Role Description

The Frontier Transformation Framework helps our customers become Frontier Firms: organizations where AI is part of the operating system the business runs on. The difference between a transformation and a one-off deployment is what happens after go-live. Without a deliberate improvement and optimization discipline, returns erode: adoption plateaus, agents drift, prompt libraries go stale, and high-value agents are starved while low-value ones persist. Intelligent Optimization is the operating discipline that makes AI value compound over time rather than dissipate.

We are seeking an Intelligent Optimization Lead, Continuous Improvement to make AI value compound across strategic customer engagements. In this role, you will establish and run the Intelligent Optimization Framework as a permanent operating rhythm, grounded in kaizen and strong facilitation, that redesigns and reruns workflows to outcomes. You will solve the last-mile problem, embedding what gets built into how work actually gets done through standard work, clear ownership, and an execution cadence that makes new ways of working stick, working directly with business owners, operators, champions, and the Value, Skilling, Change, and engineering leads.

This is a role for people who are energized by making change hold rather than launching it, who can read measurement signals and turn them into the next round of improvement, and who believe a program that ships once and leaves is just a release, not a transformation. You are designed to fade into a customer counterpart who owns the improvement rhythm after the engagement ends. If you are excited by turning AI deployments into value that compounds cycle after cycle, this role is for you.

Responsibilities

• Establish and run the Continuous Improvement Framework as a permanent, always-on operating rhythm rather than a one-off activity, grounded in kaizen and strong facilitation.
• Redesign and rerun workflows to outcomes, running structured improvement cycles in which each measurement cycle feeds and improves the next.
• Solve the last-mile problem by embedding new ways of working into standard work, clear ownership, and a disciplined execution cadence.
• Read the Copilot Dashboard and other measurement signals to find where usage is shallow, which roles are stuck, and where behavior change is or is not landing, and convert those signals into prioritized improvements.
• Continuously refine prompt libraries, enablement materials, and agent configurations based on usage data and Work IQ behavior signals.
• Detect and correct agent drift, retire or rework low-value agents, and direct further investment toward high-ROI agents.
• Establish standard work, ownership, and review cadences that make improvements durable and repeatable across teams.
• Facilitate improvement events and retrospectives that treat friction and feedback as inputs to the next cycle rather than one-off fixes.
• Capture reusable improvement patterns and playbooks that raise the quality and speed of every subsequent cycle.
• Transfer the continuous improvement discipline, cadences, and tooling to the customer's own people so the rhythm is sustained after the engagement fades.
• Recommend and drive the discontinuation of workflows, agents, and enablement assets that are not returning value to ensure capacity flows to the most important value.

Success in this role looks like:

• AI value compounds cycle after cycle rather than plateauing after initial deployment.
• Adoption deepens, agents stay tuned and current, and prompt libraries and enablement stay fresh.
• New ways of working stick because they are embedded in standard work, ownership, and an execution cadence.
• Investment flows to high-ROI agents while low-value ones are reworked or retired.
• The customer runs the continuous improvement rhythm independently after the engagement fades.
• Low value work is deprioritized and stopped. Subtraction is accepted by the customer as a normal part of the improvement rhythm.

Qualifications

• Master's Degree in Business, Engineering, Operations, Information Systems, or related field AND 4+ years experience in continuous improvement, operational excellence, process improvement, or transformation delivery OR Business, Engineering, Operations, Information Systems or related field AND 6+ years experience in continuous improvement, operational excellence, process improvement, or transformation delivery OR equivalent experience.

Preferred Qualifications

• Proven track record running continuous improvement or operational excellence programs that delivered sustained, measurable results.
• Hands-on experience with kaizen, Lean, or comparable improvement methodologies and facilitation of improvement events.
• Experience establishing standard work, ownership models, and execution cadences that make change durable.
• Experience with quality assurance or evaluation practices for production systems.
• Ability to read operational and adoption metrics and translate them into prioritized improvements.
• Strong facilitation and stakeholder-management skills across business and technical teams.
• Ability to work directly with operators and business owners to embed new ways of working into daily operations.
• Strong problem-solving skills in ambiguous, fast-moving environments.
• Lean, Six Sigma (Green/Black Belt), or equivalent continuous improvement certification.
• Experience improving AI or automation solutions in production, including managing model, prompt, or agent performance over time.
• Familiarity with Microsoft Copilot adoption and the Copilot Dashboard in Viva Insights, and with using usage signals to drive improvement.
• Understanding of agent operations, including drift detection, evaluation, and lifecycle management.
• Experience linking improvement work to value and P&L outcomes.
• Industry depth in one or more sectors such as Financial Services, Healthcare, Manufacturing, Energy, or Government.
• Experience transferring a continuous improvement capability into a client's own organization.

Compensation

The typical base pay range for this role across the U.S. is USD $101,800 - $193,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $126,100 - $207,600 per year.

Application Process

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Equal Opportunity Employer

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.