Senior engineer, 13+ years in distributed systems. I build anti-financial-crime systems at a Nordic bank by day, and solo-ship agentic-AI products โ and win hackathons โ by night.
I care about AI that explains its reasoning, leaves an audit trail, and actually works in production.
- ๐ฆ Software Engineer @ Swedbank โ anti-financial crime & AML
- ๐ค Building agentic AI on Azure AI Foundry, A2A, and MCP
- ๐งฎ Researching GPU & quantum compute โ q1729, the quantum taxicab
๐ก๏ธ ARGUSMulti-agent compliance intelligence on Azure AI Foundry Microsoft Agents League โ AI Skills Fest 2026 ยท Reasoning Agents track โ
problem> Manual KYC/AML review doesn't scale, and unaudited AI decisions don't survive a regulator's questions. approach> Five specialist AI agents, coordinated over the A2A protocol on Azure AI Foundry, run KYC, AML, and risk screening โ every finding grounded in cited regulation via Foundry IQ, every decision backed by a full audit trail. Built solo; one of three Hack for Good winners. Studied Foundry IQ before building ARGUS, then competed in the Agents League Reasoning Agents track โ and won Hack for Good (1 of 3). Foundry IQ Learned before building โ ยท Reasoning Agents Track participant โ
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๐ DRIFTRelease intelligence for GPU & AI infrastructure OpenAI Build Week ยท Devpost โ
problem> GPU/AI-infra changelogs are noisy and scattered โ teams miss the one release that breaks their pipeline. approach> An agentic pipeline that turns noisy changelogs into cited, bounded, inspectable release briefings for GPU and AI-infrastructure teams โ grounded and source-linked, never hand-wavy.
Repository โ ยท Watch demo โ ยท Live app โ ยท API docs โ ยท Devpost โ |
๐ฌ Banker's WrappedAI-powered financial storytelling Backblaze Generative Media ยท Devpost โ
problem> Nobody reads a transaction CSV for fun โ but everyone will watch a 60-second recap of their own year. approach> Spotify Wrapped, but for your bank account โ an agentic pipeline that turns a transaction CSV into a personalized 60-second narrated recap video. Three of four AI steps route through the Genblaze SDK; Backblaze B2 is the source of truth, storing 14 artifacts per session with a SHA-256 apiece, so share links survive a full backend redeploy.
Repository โ ยท Watch demo โ ยท Live app โ ยท API docs โ ยท Devpost โ |
๐ง ContinuumDurable incident memory for cold-started agents problem> An agent killed mid-incident normally loses all context โ and starts the investigation over from zero. approach> Agentic incident-response memory that survives the agent being killed mid-incident โ execution state lives in CockroachDB, not process memory, so a cold-started agent resumes from the exact interrupted step.
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ARGUS: Compliance Infrastructure That Believes Financial Access Is a Human Right โ techcommunity.microsoft.com ยท Guest post (July 2026)
Microsoft published my full write-up on the Educator Developer Blog, including how ARGUS coordinates five agents over A2A with citation-grounded risk scoring.
Lee Stott ยท Microsoft in #agentsleague (theme-aware image)
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Ramanujan's mathematics meets the NVIDIA stack
problem> How fast can a 100-year-old series actually run on today's silicon โ classical and quantum? approach> How fast can a GPU compute ฯ โ classically, and as a quantum computer? An end-to-end study from consumer RTX to datacenter H100 (CUDA C++ and CUDA-Q/cuQuantum), with an AI layer that writes up what the numbers actually show.
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๐งฉ Agentic AI & Enterprise Intelligence I design AI systems with Azure AI Foundry, Foundry IQ, multi-agent orchestration, Agent-to-Agent (A2A) communication, and RAG with hybrid search โ built to be explainable, grounded, and production-ready.
๐๏ธ Distributed Systems & Backend Architecture 13+ years building scalable platforms with Java (Spring Boot, Quarkus) and Python (FastAPI) โ microservices, NoSQL, event-driven systems, and hybrid cloud across AWS, Azure, and OpenShift.
โ๏ธ AI Infrastructure, Performance & Compute I work at the infrastructure layer behind modern AI โ GPU computing, NVIDIA CUDA, model serving, vector search, and performance engineering.
๐ก Reliability, Observability & Platform Engineering I build resilient systems with Azure Functions, Service Bus, OpenTelemetry, Application Insights, and KQL โ telemetry pipelines that hold up to enterprise-grade reliability and governance.
Languages & Frameworks
Agentic AI & LLM
Cloud & Infrastructure
AI Infra, GPU & Observability
2025 โ Present ยท Software Engineer ยท Swedbank โ Stockholm, Sweden Anti-financial crime ยท AML platforms ยท 95%+ test coverage across a unified multi-module architecture
2021 โ 2025 ยท Senior Java Developer ยท Viaplay Group โ Stockholm, Sweden Media & streaming platforms on AWS + Kubernetes ยท ~30% performance and ~40% delivery-speed gains
MarโSep 2021 ยท Software Developer ยท Expleo Technology Nordic โ Gothenburg, Sweden Domain-driven microservices ยท ~50% faster onboarding via documentation & workflow diagrams
2012 โ 2021 ยท Senior Software Engineer ยท 8 yrs 6 mos ยท IBM โ Sydney & Pune Regulated banking APIs for Westpac ยท ~25% response-time gains ยท Jenkins/Bamboo delivery modernization
- q1729 โ Ramanujan ร the NVIDIA stack โ CUDA-Q/cuQuantum simulation with an AI analysis layer
- llm-qlab โ LLM quantization benchmarks on consumer GPUs โ speed, VRAM, and quality trade-offs
- pythonic-algorithms-lab โ CPU vs GPU algorithm benchmarking with empirical Big-O profiling (CuPy + Numba CUDA)
- iq-series โ Hands-on Microsoft IQ notebooks โ Foundry IQ, Work IQ, Fabric IQ
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- NVIDIA Certified Professional: Agentic AI (NCP-AAI) โ NVIDIA
- Machine Learning and AI Foundations: Prediction, Causation, and Statistical Inference โ LinkedIn Learning Community
- IBM Machine Learning Essentials โ IBM
- Python for Data Science โ IBM
- Kubernetes Administration (LFS458) โ The Linux Foundation
Full certification list on LinkedIn โ
Building trustworthy AI systems that explain their reasoning, leave an audit trail, and actually work in production.
If that's the kind of problem you're working on โ I'd love to talk.
github.com/iarjunganesh ยท arjunganesh.dev