A cross-section of backend engineering and AI automation work — from distributed financial platforms to private cloud infrastructure.
A distributed, multi-stage loan processing system built on modular Django service layers — with rule-driven validation pipelines, Pydantic schema enforcement, and webhook-driven integrations for regulatory-compliant workflows.
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An AI-driven platform automating extraction and transformation of balance sheets, income statements, and cash flow data — cutting manual processing time by 95% and error rates by 90% through active learning and clustering algorithms.
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A full-stack private cloud setup integrating Django, local LLMs via Ollama, Stable Diffusion, Nextcloud storage, and WireGuard VPN — alongside AWS Lambda, EC2, ECS, and RDS for cloud-native capability building.
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A real-time event ingestion and routing platform handling multi-source webhook integrations with signature validation, deterministic retry logic, and structured exception pipelines across distributed services.
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A cost-optimised, event-triggered data processing pipeline using AWS Lambda, SQS, and RDS — with GitHub Actions CI/CD, CloudWatch observability, and IAM security controls for a regulated financial services client.
Discuss a similar project →A retrieval-augmented generation system enabling natural-language querying of large unstructured document corpora — built with LangChain, LlamaIndex, and Claude AI, deployed on private infrastructure with strict data residency controls.
Discuss a similar project →Bring us the hard engineering problems — distributed systems, AI automation, or cloud infrastructure. Let's build something that works at scale.