Clarify the real problem
Separate symptoms from causes before committing to a solution.
Portfolio research programme / 2024–2026
Senior Program Manager · Azure Commerce · Agentic AI
Dheemanth Rajkumar
How do we turn cloud-scale complexity into clear, reliable systems?
I connect business, engineering, live-site operations, and sales engineering to improve Azure Commerce. My work spans service architecture, agentic AI, telemetry, capacity, billing, and global delivery.
Records10
Case studies06
Reserved04
FormatDossier
Illustrative portfolio map. Each line resolves into one self-contained project record.
Azure experience2009–Present
Case studies06 published
Delivery reach1,000+ engineers
Graduate educationM.S. Applied AI · USD
01Project index
Six case studies, with four spaces reserved for work still being documented.
The published dossiers show challenge, approach, an illustrative model, and contribution. Reserved entries keep the portfolio structure ready without overstating unfinished work.
P01
RAG OnboardingEnabled grounded LLM access to business data through early framework adoption.
AI / Data AccessCase study↗
P02GHCP Adoption TelemetrySkill-level telemetry for internal adoption and ROI insights.
Telemetry / Low CodeCase study↗
P03BETA-MINDA research program for measuring whether AI preserves human agency.
AI Research / EvaluationResearch design↗
P04Cloud CapacityQuota management at global scale across 100+ Azure services.
Cloud / CapacityCase study↗
P05Sales EngineeringConnecting Azure migration, FinOps, and commercial strategy to executive outcomes.
Azure / Commercial StrategyCase study↗
P06Global Support DeliveryLaunched two Azure delivery sites and the operating system behind them.
Azure / Service OperationsCase study↗
P07Reserved Project 07Reserved for a future case study.
Future / ReservedReserved↗
P08Reserved Project 08Reserved for work still being documented.
Future / ReservedReserved↗
P09Reserved Project 09Reserved for an evidence-led project record.
Future / ReservedReserved↗
P10Reserved Project 10The final reserved space in the collection.
Future / ReservedReserved↗
02Working principles
Four principles guide how the work is framed and evaluated.
Good outcomes matter, but so do the quality of the decisions, the clarity of the system, and what remains useful after launch.
Make decisions visible
Document tradeoffs so the work can be understood, challenged, and improved.
Build for actual use
Prefer observable behavior and useful outcomes over decorative complexity.
Leave capacity behind
Create systems that remain legible and adaptable after delivery.
03Experience
Sixteen years across Azure commerce, customer outcomes, and operational scale.
A career connecting platform architecture with the financial, operational, and human systems required to run cloud services globally.
CompanyMicrosoft
DomainAzure Commerce
LocationRedmond, Washington
Tenure2009–Present
Sep 2021–Present
Senior Program Manager
Redmond, Washington · HybridBlend business, engineering, live-site, and sales-engineering perspectives to improve and unify transactional experiences across Azure Commerce.
Lead commerce service architecture reviews, AI feature engineering, and continuous improvement through agentic harness and loop engineering.
- Azure Commerce architecture
- Agentic AI feature engineering
- Live-site and sales engineering
Dec 2017–Sep 2021
Partner Technical Advisor
Global Azure deliveryHelped enterprises convert complex Azure commerce, billing, identity, and capacity challenges into predictable executive outcomes through rigorous technical and economic analysis.
Built telemetry frameworks for decisive action, improved operational resilience, and launched delivery centers in Costa Rica and Colorado Springs supporting more than 1,000 engineers.
- Executive technical advisory
- Capacity and resource optimization
- Global delivery leadership
Nov 2009–Dec 2017
Support Engineering
Azure Commerce, Subscriptions & BillingResolved complex Azure cloud infrastructure, subscription, and billing issues while translating emerging operational patterns into clear business needs and action plans.
Led small rotational teams and guided projects from incubation through operational maturity.
- Complex issue resolution
- Pattern and risk analysis
- Project incubation
EDU
Shiley-Marcos School of Engineering · University of San Diego
May 2024–Jan 2026
Master of Science in Applied Artificial Intelligence
Shiley-Marcos School of Engineering · University of San DiegoGraduate study reinforcing the technical foundation behind applied AI program design, evaluation, data grounding, and responsible adoption.
04Credentials & recognition
Formal AI education, verified learning, and recognition across product, Azure, and technical leadership.
The evidence combines graduate study in Applied Artificial Intelligence with a curated selection from 18 public Credly badges.
Graduate degreeM.S. Applied AI · USD
Verified badges18
Primary domainsAI · Product · Azure
Verify badges on Credly ↗AI / 2026
MBO AI+CI Foundations Certified
Microsoft Business Operations
Recognition / 2024
Global Hackathon Executive Challenge Winner
The Microsoft Garage
Product AI / 2023
AI for Product Management
Pendo
Analytics / 2023
Product Analytics Certification
Pendo
Product / 2023
Product-led Certification
Pendo
Leadership / 2021
Technical Leadership Development Program — Alumni
Microsoft MCAPS Academy
Azure Commerce / 2021
WW Azure Technical Community — Commerce SME
Microsoft technical community
Azure / 2020
Microsoft Certified: Azure Fundamentals
Microsoft
Additional verified work includes Microsoft Global Hackathons from 2020–2025, Product Management Basics, Pendo Super Certified, Kepner Tregoe Practitioner, and Azure Subscription & Billing Support.
05Outside work
Outside work, curiosity moves between research, making, and the outdoors.
Independent AI exploration sits alongside two ways I reset away from a screen: E-skates and snowboarding.
BETA-MIND
Exploring how persistent AI use may change independent reasoning, creativity, socialization, and decision accountability.
Open research dossier ↗AI experiments
Turning early ideas into testable frameworks, telemetry models, and working prototypes that make abstract questions observable.
Review selected projects ↑Applied AI
Extending practical experience through graduate study, product education, technical communities, and hands-on experimentation.
Review credentials ↑E-skates
A fast, focused way to get outside, explore, and exchange screen time for movement.
Snowboarding
My home mountain is Crystal Mountain in Washington—where winter weekends mean fresh air, elevation, and the next run.
Crystal Mountain / Current--°FLoading weather…
06 / About
I turn cloud-scale ambiguity into clear, reliable systems.
This portfolio connects selected work with the operating experience behind it: Azure commerce architecture, customer economics, live-site resilience, telemetry, global delivery, and applied AI.