Alfa Laval

A seven-year, four-project engagement with Alfa Laval. From modernizing legacy test automation on the Anytime project to architecting their flagship GenAI platform (Alva), contributing across QA, DevSecOps, and AI systems.

Years engaged

Distinct projects

750%

Pipeline speed-up

10+

LLMs orchestrated

Overview

Alfa Laval — the Swedish industrial giant in heat transfer, separation, and fluid handling — is the client I’ve contributed to longest. Across seven years I’ve delivered on four distinct initiatives, progressing from hands-on QA transformation into full AI systems architecture.

The common thread: shipping production-grade quality and production-grade AI at a company where downtime costs real money.

Project 4 — Alva / Alfabeta Platform · AI Systems Architect (2024 – Present)

Alfa Laval’s flagship enterprise GenAI platform. I architected the full stack end-to-end.

What I shipped

A ReAct-style reasoning agent on LlamaIndex with FastAPI, orchestrating 10+ LLMs (GPT-4o, Claude Sonnet/Opus, Mistral, Llama, Grok, DeepSeek) through Azure AI Foundry
Full RAG pipeline — document parsing (PDF, DOCX, PPTX, XLSX, OCR) → chunking → Azure OpenAI embeddings → pgvector retrieval
.NET 8 orchestrator following Clean Architecture, brokering streaming responses end-to-end (Agent → API → React UI)
Azure infrastructure — fully defined in Bicep IaC, with per-service RBAC, image-promotion pattern for ACR prod isolation, async Azure Functions for document embedding
Observability — OpenTelemetry tracing, Application Insights, consolidated coverage across .NET (xUnit) and Python (pytest)
Unified CI/CD across 7 services — single Alva.yaml with Detect / Build / Deploy / E2E stages, selective-component builds, parallel fan-out, QA sign-off gates
Admin Configuration Panel — agents, models, terms, policies CRUD (React + .NET API)

Why it matters: most enterprise GenAI stalls at the prototype. This one reached production because it was designed for ops on day one.

Project 3 — AzSupport · Senior SDET / DevSecOps (Feb 2022 – Mar 2023)

Supported cross-functional DevSecOps initiatives across Alfa Laval’s Azure footprint.

Set up secure CI/CD pipelines with automated tests and vulnerability scans baked into every deploy
Configured Azure DevOps agents for diverse workloads (Windows, Linux, containerized)
Collaborated with security specialists to embed OWASP and supply-chain best practices directly into pipelines
Hardened test automation for regulated environments

Project 2 — OneIB · Senior SDET (Feb 2021 – Feb 2022)

Built the scalable automation framework that became a reference implementation used across subsequent Alfa Laval projects.

Developed a C# + Playwright framework for rapid UI and API validation
Integrated into Azure DevOps CI/CD — parallelized execution, pull-request gated builds
Reduced release cycle time by integrating automated validation at every merge
Handed the framework pattern to the broader engineering org as a template

Project 1 — Anytime · Test Automation Engineer (Feb 2018 – Feb 2020)

The first engagement — a rescue job on an aging test automation stack.

Migrated from legacy tooling to a Selenium-based C# framework
Rewrote test execution principles from the ground up — both solution architecture and test case management
Established Azure DevOps pipelines for rapid feedback loops
Result: stability up ~300%, execution time down 750%, initial setup time down by another 500%

Why Alfa Laval keeps calling

Seven years, four projects, steadily expanding scope — from automation engineer to systems architect. The pattern isn’t coincidence. When you build something that works, the next project lands on your desk.