Resume
Tan Tran
Data & AI leader · Solution architect · Founder
Currently open to Data & AI leadership roles and consulting engagements, including international and relocation. Writing at tantran.dev about AI and engineering practice in the meantime.
Company names, dates by month and references are deliberately left off this public page. Ask and I will send the full version — I would rather know who is reading it. Request the full CV
In one paragraph
Twenty years in software: from writing it for companies whose products depended on it, to building and running a company of my own past a hundred people, to now leading enterprise Data & AI — strategy, the teams to deliver it, and production systems built on machine learning and GenAI. I have carried a payroll that had to come out of last month's revenue, and that constraint still shapes how I work: ship things that earn their keep.
Experience
Set enterprise AI strategy and build the teams and governance to deliver it in production.
- Own the Data & AI strategy and roadmap end to end: data governance, analytics and KPIs, GenAI use cases, and custom ML, each tied to a measurable outcome.
- Stand up an AI Center of Excellence and advise senior leadership with business cases and ROI.
- Ship production AI — machine learning, GenAI, RAG, agentic automation — into enterprise systems on Azure and AWS, with responsible-AI controls built in.
- Currently architecting a credit and risk decisioning ML solution end to end.
Built a technology services company from nothing to a profitable business of over 100 people, without outside funding.
- Grew from zero to 100+ employees and past $1M in profitable annual revenue, bootstrapped throughout.
- Quadrupled the delivery team from 20 to 80 engineers in six months to meet demand, without losing quality.
- Stood up a fully operational overseas subsidiary from scratch in under twelve months.
- Held full profit and loss ownership, including through the COVID-19 period.
- Delivered into banking, insurance and energy — long procurement cycles and hard compliance.
Fourteen years from hands-on engineering to technical pre-sales and solution architecture, mostly for financial services.
- Ran the full solution cycle — discovery, design, proof of concept — then took prototypes through to MVP with commercial and delivery teams.
- Eight years in financial services for banks and insurers, from mobile banking to credit and risk platforms.
- Earned approved-vendor status with large enterprise and public-sector clients, and stayed the trusted technical contact through sales and delivery.
Capabilities
- Data & AI
- Strategy and governance, machine learning, GenAI and LLMs, RAG, agentic AI, MLOps and responsible AI
- Architecture
- Solution and enterprise architecture, cloud on AWS and Azure, technical pre-sales, proof of concept to MVP
- Data platforms
- Lakehouse and pipelines — Databricks, Snowflake, Spark — with analytics and BI
- Leadership
- Building and leading AI teams, delivery and program management, P&L, scaling to 100+
- Sectors
- Banking, insurance, government, enterprise technology
Outside work
Ironman finisher. I think about business the same way: it needs endurance, discipline, and knowing when to stop. I call myself a lazy triathlete to keep the last part in view.