Software Engineer · Technical Lead · Builder

Sakir SatheCosta Rica

Building reliable software across .NET, cloud, data and AI.

I’m a software engineer and technical lead with more than fourteen years of experience building, modernizing and operating complex software systems.

I remain hands-on across architecture, backend engineering, cloud, data and AI. Alongside that work, I develop reusable tools and write about what I learn while building systems.

Explore Engineering Read Writing

focus.mapstack: microsoft / cloud / ai

Experience: 14+ years
Primary: C# · .NET · Azure
Current focus: Retrieval · Agents
Based in: Costa Rica

01Engineering

Engineering across the stack

I enjoy engineering problems that cross boundaries — application architecture, backend systems, cloud infrastructure, data, search, AI and developer experience.

Engineering overview

.NET & Backend Engineering

Service design, APIs and the background work that keeps systems moving.

C# / .NET / ASP.NET Core / EF Core / REST / gRPC / Background processing / Microservices

Cloud & Azure

Hosting, identity, secrets, telemetry and delivery on the Azure platform.

Azure App Service / Functions / Storage / Key Vault / Managed Identity / Application Insights / Azure DevOps

AI, Search & Retrieval

Grounding language models in real data through search and retrieval.

Azure OpenAI / Azure AI Search / Semantic search / Vector search / RAG / MCP / AI agents

Data & Integration

Moving, shaping and reporting on data between systems.

SQL Server / Azure Data Factory / ETL / SSIS / Fabric / Power BI / REST / GraphQL

Frontend Engineering

Interfaces for data-heavy, workflow-driven applications.

Blazor / React / Angular / TypeScript

Technical Leadership

Design decisions, review culture and keeping production healthy.

Architecture / Technical design / Code review / Mentoring / CI/CD / Production support / Root-cause analysis

Problems I like working on

Developer Infrastructure: Tools that remove repetitive engineering work and make systems easier to test, understand and operate.
AI-Native Software: Practical ways of combining software engineering, retrieval, agents and language models without sacrificing reliability.
Enterprise Modernization: Turning complex or legacy systems into maintainable, observable and automated platforms.
System Integration: Connecting APIs, data platforms, cloud services, enterprise systems and physical devices.
Architecture & Reliability: Understanding how systems behave in production and designing them to fail less often.

02Work