Equally at home in TradFi analytics and onchain systems. Two flagship SaaS — stox.my and TradeClaw — live in production. I think like a business owner: every system optimises for user delight, real-time correctness, and the unit economics of scale.
What four years at the intersection of finance and AI actually looks like.
$10M → $200M
AUM growth
Inter-Pacific Asset Management · ~1.5 years
$50K → $200K
Monthly net profit
Trader portal · within 1 year
~400%
Marginal profit lift
Salmi Niaga · systems and unit-economics discipline
15+
Production apps
Dashboards, signal bots, RAG agents, contest engines
1.4s → 80ms
p50 latency tuned
SprintBo bot /ranking · D1 + KV across 3 surfaces
< $5
Monthly infra cost
SprintBo · cron-driven, idempotent, zero ops headcount
What I do
Three things, deeply. Everything else is a side project.
01
Trading platforms & investor analytics
Stock analytics SaaS, multi-factor screeners, watchlists, AI-assisted alpha discovery. Real-time pricing pipelines, hand-written SQL, sub-100ms reads on hot queries.
Real-time market data ingestion + ranking
Momentum + fundamentals factor screening
Investor-facing dashboards tuned for data density
02
Community platforms & multi-agent bots
Community apps with points, leaderboards, and social loops — like the Gold Traders portal. Contest platforms that pull live standings from sources with no public API. And a different kind of chatbot: dynamic, multimodal agents that talk to each other while humans watch and step in.
Community apps — points, leaderboards, social automation
Contest engines with API-less data scraping
Multi-agent chat — bots converse, humans observe
03
End-to-end ownership
Spec, design, code, deploy, monitor, iterate. Smallest useful MVP, validate with real users, then scale. Highest-leverage work first. Founder posture — even inside a bank.
Investment desk, then engineering, now both at once.
2024 — now
Full Stack Engineer & AI Trading Systems · RM Investment Bank Ltd
Built a trader portal (apps, AI signal tools, leaderboards, community automation) that lifted average monthly net ~$50K → $200K within 1 year — replaced what would have been a ~3-engineer + PM build. 15+ production apps across investor dashboards, signal bots, RAG agents, weekly contest engines.
2023 — 2024
Founder / Technical Lead · Tibyan AI Sdn Bhd
Founded an AI-first venture. Secured seed investment from Cradle and Nexea. Owned product, engineering, and GTM end-to-end across Python, TypeScript, React, PostgreSQL, AWS — first-engineer posture from day one.
Drove ~400% increase in marginal profit through better systems, automation, and execution discipline. Built Python analytics dashboards and reframed P&L from gross-revenue chasing to unit economics.
2020 — 2021
Investment Analyst & Data Engineer · Inter-Pacific Asset Management
Contributed to AUM growth from ~$10M to ~$200M in ~1.5 years through data-driven research and screening. Built data pipelines, factor models, and analytics dashboards in Python and SQL.
Best Shariah Equity Malaysia 2020 — Lipper / Refinitiv
2016 — 2020
Finance Executive · AmanahRaya Trustees Berhad
Fund accounting, treasury operations, financial modelling. Excel/VBA automation that compressed reporting cycles — first hands-on exposure to the data shape behind investor analytics.
Stack
The tools I actually use to ship — not a fashion show.
TypeScript & Node (primary, ~5y)
Node.js
React 19
Next.js
Vite
Hono
Express
REST APIs
Hand-written SQL
React Frontend
React 19 hooks
Suspense
Tailwind
Data-dense dashboards
Databases
PostgreSQL
MySQL
SQLite / D1
MongoDB
Redis-style KV
Numbered .sql migrations
AWS & Containers
EC2
ECS
Lambda
S3
RDS
IAM
Docker
GitHub Actions
Terraform
Crypto / Onchain
Smart contracts (Canton)
keccak256
EVM signing
L1 / L2 patterns
Exchange APIs
Python & Backend
FastAPI
Flask
Django
Pandas
scikit-learn
Factor models
ETL
Edge & Distributed
Cloudflare Workers
D1
KV
R2
Durable Objects
Browser Rendering
Cron Triggers
Apache Kafka
AI & LLM
Anthropic Claude
Agent SDK
MCP
OpenAI
HuggingFace
RAG
bge-m3 embeddings
Prompt + context engineering
Contact
Have a problem at the intersection of finance, AI, and infra?
I read every message and reply within two working days. If it is not a fit, I will say so directly and probably point you to someone who is.