Industrial software & applied AI
I build software for
AI & Full-Stack Software Engineer at Lean Automation. I own the architecture for an industrial IoT platform that runs inside air-gapped customer infrastructure in the oil & gas sector, and I lead a team of three. Event-driven microservices in ASP.NET Core and Node.js, sensor telemetry over MQTT and Kafka, integration with plant historians and field instrumentation (AVEVA PI, PI Vision, control loops), and applied AI where it earns its place.
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I N D U S T R I A L · S O F T W A R E
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I N D U S T R I A L · S W Timeline
Professional Journey
Experience across AI engineering, full-stack product development, and applied medical AI research.
AI & Full-Stack Software Engineer
Feb 2025 – PresentOwn the architecture for a production industrial IoT platform delivered into air-gapped customer infrastructure in the oil & gas sector, and lead a team of three engineers.
- ›Own platform architecture and lead a team of three engineers
- ›Decomposed a monolith into independently deployable ASP.NET Core, Node.js and NestJS services
- ›Designed the event-driven data layer over Kafka and MQTT for field sensor telemetry
- ›Integrated plant historians (AVEVA PI, PI Vision) and field instrumentation, working across control loops with instrumentation and loop-performance engineers
- ›Built on-premise RAG pipelines and a fine-tuned LLM engineering co-pilot — no external model APIs
- ›Delivered the full stack into air-gapped environments with Docker, Kubernetes and an offline registry
- ›Designed operator interfaces aligned to existing HMI conventions
Software Engineer — AI/ML
Feb 2024 – Feb 2025Built AI/ML features and full-stack functionality across the platform — model development, data pipelines, and the services around them.
- ›Developed ML models and data pipelines feeding production features
- ›Built and shipped full-stack functionality across React/Next.js and Node.js services
- ›Implemented CI/CD with GitHub Actions and Docker for reliable releases
- ›Built real-time dashboards for KPI and anomaly monitoring
Associate Software Engineer
Jan 2023 – Jan 2024Delivered production web platforms and automation pipelines across analytics, APIs, CI/CD, and deployment workflows.
- ›Delivered production full-stack applications
- ›Implemented GitHub Actions + Docker CI/CD for zero-downtime deployments
- ›Automated reporting via SQL procedures and APIs
- ›Built real-time dashboards for KPI and anomaly monitoring
Research Assistant
Mar 2024 – Feb 2025Led thesis research on medical AI for brain tumor analysis, focusing on model design, dataset engineering, and publication-ready outputs.
- ›Developed a Dual-Head Neural Network (DHNN) for tumor type + grade prediction
- ›Built end-to-end MRI preprocessing pipelines with OpenCV and Pandas
- ›Achieved 93.2% classification accuracy with EfficientNetB0 backbone
- ›Co-authored and submitted work to Elsevier Results in Engineering
Bachelor of Science in Computer Science (BSCS)
Mar 2021 – Jan 2025CGPA: 3.56 / 4.0. Focused on AI/ML systems, software engineering, and data-driven problem solving.
- ›Thesis: Multi-Class Brain Tumor Classification and Grade Estimation using DHNN
- ›Coursework: AI, ML, DSA, DBMS, Operating Systems, Distributed Systems
- ›Built research and production projects spanning healthcare and industrial AI
Portfolio
Featured Projects
Production industrial software and on-premise AI systems, alongside applied research. Built to run in real, constrained environments.
Industrial IoT Platform — Oil & Gas
Distributed platform ingesting live field-instrumentation telemetry through event-driven microservices, integrated with plant historians (AVEVA PI, PI Vision). Decomposed from a monolith into independently deployable ASP.NET Core, Node.js and NestJS services and delivered into air-gapped customer infrastructure.
Industrial AI Co-Pilot — On-Premise RAG & Fine-Tuned LLM
Fine-tuned LLaMA 3.2 with a retrieval pipeline so answers cite proprietary sources rather than model memory. Multi-step tool-calling via LangGraph, served through FastAPI. Fully on-premise — no external model APIs.
VAE-LSTM Fault Detection
Unsupervised anomaly detection for industrial equipment where labelled failure data is scarce. VAE + LSTM over multivariate sensor streams with calibrated reconstruction-error thresholds, served via FastAPI with real-time dashboards.
Brain Tumor Classification — Dual-Head Neural Network
Dual-Head Neural Network on an EfficientNetB0 backbone for simultaneous multi-class tumour classification and grade estimation from MRI (4.0M parameters, ~15ms inference). Manuscript under review at Elsevier Results in Engineering.
Encrypted Traffic Fingerprinting
Reproduction and extension of IEEE CNS 2019 work on fingerprinting encrypted voice-assistant traffic — end-to-end feature extraction and classification over network captures, with a public, reproducible repository.
Writing
Latest writing
Technical deep-dives on industrial software engineering, event-driven architecture, and applied AI in constrained environments.
Building AI-Powered Predictive Maintenance Systems for Industrial IoT
A deep dive into building VAE-LSTM pipelines for predictive maintenance — the architecture, the engineering trade-offs, and what it takes to deploy industrial ML into constrained environments.
Deep Learning for Medical Imaging: Brain Tumor Classification with CNNs
How a dual-head neural network on an EfficientNetB0 backbone reaches 93.2% accuracy in brain tumor classification. Complete methodology and evaluation from the study.
Causal AI for Industrial Anomaly Detection: Beyond Correlation
Why causal inference beats correlation for industrial anomaly detection — identifying root causes instead of just flagging symptoms, and moving from reactive alerts toward proactive diagnosis.
Currently
On the workbench
What I'm actively working on right now — no roadmaps, just the things in front of me.
air-gapped-delivery
Hardening zero-downtime rolling updates and offline image registries for Kubernetes in air-gapped environments.
on-prem-copilot
Extending the on-premise RAG co-pilot — sharper retrieval grounding and tool-calling for plant engineers.
telemetry-ingestion
Event-driven MQTT/Kafka ingestion for field sensor telemetry, tuned for reliability over throughput.
writing-series
A weekly technical writing series on industrial software engineering, starting with air-gapped Docker.