Roshan Lamichhane
Full-stack engineer building AI systems and backend infrastructure for data-heavy products.
I design APIs, async pipelines, and agentic systems — from a quant trading platform to developer tools with thousands of users. I ship fast, measure what matters, and own systems end to end. Currently looking for strong software engineering opportunities.
- Role
- Full-Stack Engineer
- Focus
- AI · Backend · Data
- Now
- Founding Eng @ Amara Capital
- Based in
- NYC
Projects I've shipped
A few systems I've designed and built end to end — from a quant trading platform to open-source developer tools.
Kairos
AI-powered quant backtesting platformAI-powered quant backtesting platform
PythonFastAPICeleryRedisSqliteWorker
Thread-safe SQLite execution engineThread-safe SQLite execution engine
PythonSQLiteConcurrencyThreadingiFetch
Resumable differential file syncResumable differential file sync
PythonNetworkingDistributed SystemsParallelism
Specializations
Four areas where I do my best work. The common thread: systems that have to stay correct and fast under real load.
AI systems & agents
Agent control loops, tool interfaces, and evaluation harnesses that stay reliable outside the demo.
Backend & distributed systems
APIs, async pipelines, queues, and concurrency-safe data layers designed to scale under real load.
Data & pipelines
Ingestion, scraping, and ETL — cache-first services and fault-tolerant sync over messy, high-volume data.
Product engineering
Shipping MVPs fast, instrumenting them, and validating with users before over-building.
Full-Stack Engineer
NYC
I like problems where correctness and performance both matter — trading systems, data pipelines, and AI agents that can't just work in the demo.
My background spans founding-engineer roles and a contract at Citi, plus open-source tools with tens of thousands of users. I'm equally comfortable designing a database schema, tuning a hot path, and shipping the product around it.
More about meNotes on systems & shipping
Essays on the engineering I actually do — AI agents, backend performance, and building products that survive contact with reality.
Shipping MVPs That Survive
How to build and validate a product fast without creating tech debt you'll regret: scope to one core loop, fake what you can, choose boring tech, instrument from day one, and refuse to abstract before you understand the problem.
A Backend Performance Playbook
A practical guide to making backends fast: measure first, respect the real cost hierarchy of network over disk over memory over CPU, kill N+1 queries, layer caching deliberately, and know when async, pooling, and backpressure actually earn their keep.
Designing Reliable AI Agents
A systems-design view of production agents: why naive ReAct loops fall apart, how to design tool interfaces and bounded state, and where to put guardrails, retries, and evaluation so the whole thing stays trustworthy.
Building something that needs a strong engineer?
I'm open to full-time roles, freelance work, and founding-style collaborations. If the problem is hard and the bar is high, I want to hear about it.