Experience taught me how systems behave.Now I'm learning how machines learn.
I'm Mosa Rahimi—a Wharton MBA, Harvard MPA, and Amazon Leo leader. After two decades in operations, policy, and strategy, I'm deliberately building at the intersection of artificial intelligence, finance, and the consequential problems those systems create.
years across public service, policy, technology, and operations—now applied to AI
01 / 05
Based in the United StatesAmazon Leo · Project Kuiper
Systemsintointelligence.
AI & DataOperations LeadershipStrategic SystemsPublic ServiceCross-Cultural Leadership
Selected impact
Measured in outcomes.
The settings have changed—from border security to advanced manufacturing—but the work has remained consistent: make the system legible, align people, and move the mission forward.
01364K
units stowed
A non-peak Amazon record
0270+
programs coordinated
Across all 34 Afghan provinces
0312K
person border force
Scaled from 5,000 personnel
0440%+
faster reporting
Through operational systems design
AI
Why this pivot
Not reinvention for its own sake.A deliberate expansion of how I solve.
Operations taught me how large systems coordinate under pressure. Policy taught me how institutions shape outcomes. Strategy taught me where leverage actually lives. AI adds a new technical language—and a new set of consequential problems—at the intersection of finance, governance, and human-scale impact.
Machine learningAI policyApplied data scienceSystems thinking
The journey
One throughline.Many arenas.
01
June 2025 — Present
Amazon Leo (Project Kuiper)
Redmond, Washington
Coordination Supervisor
Coordinating production for Amazon Leo (Project Kuiper)—building the manufacturing systems behind the satellite constellation and translating complex aerospace operations into dependable human-scale execution.
02
2024 — 2025
Amazon
Philadelphia, Pennsylvania
SSD DC Area Manager II
Led high-volume inbound and outbound operations while building confidence, capability, and data fluency across frontline teams.
Raised a non-peak inbound record from 350K to 364K units—more than 40% above daily goal.
Turned outbound palletize into one of the network’s most consistent operations.
Built an hourly Excel performance tool and developed four process assistants.
03
2019 — 2025
Dastranj
Philadelphia, Pennsylvania
Founder & CEO
A startup with a long-term thesis: apply AI, machine learning, and computer vision to the artisan goods market—building the supply chain, brand, and operating systems to connect craft producers with global demand.
Built an end-to-end supply chain from producer relationships through fulfillment.
Company mission centers on scaling artisan goods through technology—not reinvention, but a deliberate bet on AI in a category that still runs on trust and handwork.
04
2021 — 2022
Harvard Kennedy School
Cambridge, Massachusetts
Belfer Young Leader Fellow · Machine Learning Teaching Assistant
Researched international security and science policy while helping students connect machine-learning theory to working code and final projects.
05
2019 — 2021
Team Afghan Power · Refugee Investment Network
Philadelphia · Washington, D.C.
Strategy & Development
Helped shape a five-year micro-grid and internet expansion strategy and supported capital access for refugee entrepreneurs.
06
2016 — 2018
CyraCom
New York City
Farsi–Dari Interpreter
Served as the center’s sole in-house Farsi–Dari interpreter across law, finance, medicine, and emergency response; evaluated 100+ applicants and eliminated outsourcing costs.
07
2015 — 2016
A new beginning
New York
Bank teller · Translator · Warehouse worker · Cashier
The transition period: rebuilding from the ground up in America while staying focused on education and the long horizon.
08
2010 — 2014
DOJ / ICITAP
Kabul, Afghanistan
Adviser & Senior Program Assistant
Coordinated more than 70 capacity-building programs across 34 provinces and aligned 30+ government, diplomatic, and civil-society stakeholders.
Reduced bureaucracy and overlapping projects by 20%.
Cut provincial reporting time by more than 40%.
Helped design strategic planning, international relations, and monitoring units.
09
2008 — 2010
U.S. Army Central Command
Kabul, Afghanistan
Cultural Adviser & Interpreter
Advised senior leaders on culture, law, and policy; interpreted daily for high-level delegations and taught leadership, anti-corruption, English, and technology.
10
2004 — 2008
Afghan Border Police
Kabul, Afghanistan
Aide-de-Camp · Chief of Staff
Supported the Director General as the force grew from 5,000 to 12,000 personnel across 19 provinces, 14 crossings, and four international airports.
Education
Policy mind. Business lens. Technical curiosity.
A dual graduate journey at Wharton and Harvard built the bridge between markets, institutions, analytics, and public leadership.
W
2019 — 2022
The Wharton School
MBA
Finance · Business Analytics · Management
H
2019 — 2022
Harvard Kennedy School
MPA
Public leadership · Policy · Technology
A
2009 — 2013
American University of Afghanistan
BBA
Finance
K
2003
Kabul National Police Academy
Police Sergeant
Border Police
“
My story is a humble journey of survival and triumph over some of the toughest challenges refugees and ethnic minorities encounter every day.
Citizen by choice
Resilience is not a chapter. It is the operating system.
As a refugee child in Iran, I heard stories of technological progress over the radio. Years later, after serving at the center of Afghan public institutions, I came to America and started again—from minimum-wage work, without a professional support network.
I chose to share that transition, not hide it. It shaped how I lead: with empathy for the person behind the metric, respect for the invisible work, and the conviction that capability is often waiting for opportunity.
01
Family portraitIran · The early years
02
Growing up togetherIran · Family archive
Before the boardrooms, institutions, and operations floors, there was family—the first system of resilience, responsibility, and hope.
Story 02 · The impossible dream
College was not in the cards.I refused to stop dreaming.
The chance of going to college felt nonexistent. So I worked night and day—through dust, grease, fields, and machines—while holding onto a future no one around me could promise.
The work covered my clothes. It never touched the dream.
Work was the reality.Long days · No shortcuts
College was the dream.Out of reach · Never out of sight
NIGHT / DAY
11years
Story 03 · Service under fire
I put my life on the line.The dream was bigger than the danger.
For eleven years, service meant accepting real risk—from border provinces to counter-narcotics missions across Afghanistan. Every journey carried uncertainty, but the dream was never only personal: a safer, stronger future built through institutions that could truly serve people.
The danger was real. So was the future I could see beyond it.
Mission south · In the field
Eleven years · One purpose
Risk shared · Mission forward
20042014
Story 04 · The long road to the classroom
In 1999, college was impossible.In 2022, I graduated from Wharton and Harvard.
23years from dream to dual degrees
There was no straight line—only work, service, migration, restarting, and the decision to keep going. The journey moved through the American University of Afghanistan and, eventually, two graduate programs at Wharton and Harvard Kennedy School.
Distance is not destiny. Sometimes the longest road produces the clearest purpose.
AUAFBBA · Finance · 2013
WhartonMBA · 2022
The moment afterA dream shared
Harvard Kennedy SchoolMPA · 2022
1999 The dream2013 AUAF2022 Wharton + HKS
Across cultures
Farsi Native
English Full professional
Pashto Professional working
Featured coverage
The story,on record.
NBC10 Philadelphia documented two defining moments: fighting to bring family to safety and, after escaping the Taliban, choosing to step forward publicly.
AI companies, policy organizations, and technical recruiters need artifacts—not adjectives. Here is code, analysis, and work you can inspect before we talk.
I'm looking for roles and collaborations at the intersection of artificial intelligence, operations, and policy. Start with the artifacts above—or reach out directly if you see a fit.