I'm a DevOps engineer with 4+ years in cloud, self-hosted infrastructure, and full-stack development. At Ascend Cloud Services, I've built and operated 20+ Kubernetes clusters on AWS and Azure for 10+ clients, cut cloud costs by 12–35% per project, and built the CI/CD and observability foundations for a retail client's 11 microservices.
At Bitmosys, I architected the highly available ERP behind a UK nurse staffing SaaS serving 300+ nurses — a 3-node PostgreSQL cluster, Linkerd service mesh, and a self-managed Grafana, Prometheus, and Loki stack. I'm also a DevOps Trainer at Tech Axis, mentoring students and designing hands-on labs on Kubernetes, Terraform, GitOps, and DevSecOps while co-designing an agentic AI course.
I write interactive computer science explainers, one of which drew 162 points on Hacker News. When I'm not coding, I enjoy collecting books, catching up on my favorite TV series, and hunting for the best coffee in town.
Experience
2025 — Present
DevOps Engineer · Ascend Cloud Services
- Designed and operated 20+ Kubernetes clusters on AWS and Azure for 10+ clients
- Cut monthly cloud bills by 12–35% per project by right-sizing nodes, running non-critical workloads on spot instances, and moving suitable workloads to bare metal or serverless
- Caught an AWS secret key being shipped in a client's Next.js bundle, then rolled out GitGuardian secret scanning across the organization
- Built 30+ GitHub Actions pipelines with Helm and secure IaC templates for a retail client's 11 microservices, supporting 50+ PR merges a day
- Monitored all 11 services with Prometheus, Grafana, and Loki, with dashboards and Teams/email alerting; added OpenTelemetry tracing to 3 of them
- Evaluated commercial and open-source ASR models (NeMo, Parakeet, Whisper) and fine-tuned on a few hundred hours of noisy, code-switched speech with crosstalk, reducing WER by 20–25%
2026 — Present
DevOps Trainer · Tech Axis
- Mentored 20+ DevOps students over 6 months, guiding them one-on-one through capstone projects
- Designed the curriculum and authored all labs and slide decks: Linux, Docker, CI/CD, Kubernetes, AWS, Terraform, GitOps, observability, and DevSecOps
- Built hands-on labs for Argo CD + Flagger progressive delivery on EKS, an LGTM + Jaeger observability stack, and deliberately broken Kubernetes stacks for troubleshooting practice
- Co-designed an agentic AI course covering transformer fundamentals, open-weight models, RAG and vector databases, tool use and agent harnesses, prompt caching, cost and benchmarks, and model gateways (OpenRouter, Cloudflare, Vercel)
2024
Full Stack Engineer · Bitmosys
- Architected the ERP behind a UK nurse staffing SaaS serving 300+ nurses: 3-node HA PostgreSQL cluster, Redis caching, and Nginx API gateway
- Designed a highly available permission system with audit logging for every action across 1M+ objects, so nurses could always log shifts, expenses, and progress
- Built a constraint-based shift planner (staff preferences, availability, UK bank holidays) that replaced fully manual scheduling
- Ran a Linkerd service mesh and a self-managed Grafana, Prometheus, and Loki stack; deployed with Docker, Kubernetes, and CI/CD
- Chose the frontend stack and set performance, code-quality, and design-language guidelines; mentored a junior developer and reviewed PRs
2023 — 2024
Full Stack Developer · Cango
- Developed dynamic dashboards with React, React Query, Zustand, and Tailwind CSS
- Built a reusable component library for a political survey platform
- Integrated backend APIs with PostgreSQL and Redis, and created data visualizations with Apache ECharts
- Refactored a legacy codebase into modular TypeScript for maintainability
2022 — 2023
Frontend Developer · Matrice AI
- Cut Next.js landing page time to interactive from ~2 s to under 500 ms, fixing poor FCP and layout shift
- Rebuilt the annotation dashboard in React and Tailwind CSS to align with the new UI/UX
- Added responsive layouts, accessibility, and internationalization across the dashboard
- Developed backend services for the image annotation platform on AWS, with real-time monitoring hooks
Writing
An Interactive Guide to Count-Min Sketch
Learn Count-Min Sketch: a probabilistic data structure for estimating item frequency in data streams, featuring an interactive guide and demo
An Interactive Guide to Caching Strategies
Explore popular caching strategies for improved application performance, including Cache-Aside, Read/Write-Through, Write-Back, and more
An Interactive Guide To Rate Limiting
Learn about rate limiting algorithms with interactive apps, including Token Bucket, Leaky Bucket, Fixed Window, and Sliding Window methods
Projects
Labeling Harness
Human-in-the-loop workbench that turns raw recordings into a verified speech dataset. Three recognizers draft every clip, disagreement pushes the doubtful ones to the top of a ranked queue, and one annotator checks them at keyboard speed — 61 hours and 17,000+ Nepali–English clips labeled so far.
Linite
Bulk installer for 200+ curated Linux apps across 14 distros and 11 package managers, from APT to Flatpak. Supports shareable collections, cross-device install tracking, and daily metadata sync from Flathub, Snapcraft, AUR, and Repology.
InfraWise
Models cloud vs. on-prem total cost of ownership across 8 cost categories, with multi-year projections, breakeven, and sensitivity analysis over 80+ variables.
Reading List
Team Topologies: Organizing Business and Technology Teams for Fast Flow
Matthew Skelton, Manuel Pais
Effective software teams are essential for any organization to deliver value continuously and sustainably. Provides practical, step-by-step guidance for designing organization structures and interaction patterns to maximize team effectiveness and flow.
Software Engineering at Google
Titus Winters, Tom Manshreck, Hyrum Wright
Learn how Google builds software at scale with insights into their engineering culture, practices, and tools. Covers code review, testing, dependency management, large-scale changes, and building sustainable software engineering organizations.
Designing Data-Intensive Applications
Martin Kleppmann
The definitive guide to understanding the fundamental principles behind modern data systems. Covers distributed systems, data models, storage engines, replication, partitioning, transactions, and consistency models. Essential reading for anyone building reliable, scalable, and maintainable applications.
Certifications
2020-06-01
Deep Learning Specialization
DeepLearning.AI
2020-06-01
AWS Fundamentals Specialization
Amazon Web Services