Solutions Architect / AI Engineer / Fintech Builder
π‘ AWS & Azure Certified Architect | 15+ years experience in cloud-native design, event-driven systems & AI integration
π Based in London | Founder @ Urban Folklore Ltd
JobProof | Shabdha | LinkedIn | Kavalu
| Project | Description | Stack |
|---|---|---|
| JobProof | A personal interview coaching platform β multi-model LLM orchestration with state-machine-driven session flow, evidence-grounded scoring engine with quality gates, seniority-calibrated prompt pipelines, voice-first interaction (STT/TTS), and structured claim extraction from candidate responses mapped against JD-parsed rubrics | Node.js, Python, Next.js, OpenAI/Claude APIs, Whisper/Deepgram STT, ElevenLabs TTS, Prompt Engineering |
| Shabdha Β· Website | Multilingual speech-to-text & AI writing assistant β real-time audio transcription with LLM-powered summarisation, RAG-augmented context retrieval, and multi-language support | Node.js, Python, LLM RAG stack, macOS native |
| Kavalu AI Learning Assistant | Chrome extension β AI-powered content summarisation, translation & flashcard generation using multi-model API orchestration (Gemini + GPT), with serverless backend and caching layer | AWS Lambda, Redis, Next.js, Gemini API, OpenAI API |
| Onmo Fintech Architecture | Serverless credit platform for 100k+ customers (ONMO Ltd) β event-driven pipeline design with Step Functions orchestration, real-time data streaming, and enterprise schema governance | Step Functions, Kinesis, DataZone, AWS Glue |
LLM Orchestration & Prompt Engineering β’ Multi-Model AI Pipelines β’ Voice AI (STT/TTS)
Serverless Architecture β’ Event-Driven Systems β’ RAG Pipelines
Terraform & IaC β’ Observability & Resilience β’ AI Scoring & Evaluation Systems
Languages: TypeScript Β· Python Β· C# Β· SQL
Cloud: AWS (Lambda, Step Functions, EventBridge, DynamoDB) Β· Azure (Functions, Data Factory)
AI/ML: OpenAI GPT Β· Anthropic Claude Β· Google Gemini Β· Whisper Β· Deepgram Β· ElevenLabs Β· LangChain-style agents Β· RAG pipelines Β· Prompt engineering Β· Redis vector store
DevOps: GitHub Actions Β· Terraform Β· CloudFormation Β· Datadog Β· CloudWatch
Frontend: React Β· Next.js Β· Tailwind
- π― Built JobProof β A personal interview coaching platform featuring multi-model LLM orchestration, a state-machine-driven session engine, evidence-grounded scoring with quality gates, and seniority-calibrated prompt chains. Voice-first architecture with STT/TTS integration and structured claim extraction from candidate responses.
- π§© Designed serverless credit-card platform for ONMO (UK fintech) β event-driven architecture with Step Functions orchestration achieving 60% runtime reduction.
- π Launched Kavalu AI on Chrome Store β multi-model AI pipeline (Gemini + GPT) with production-grade AWS serverless backend and Redis caching.
- π Defined enterprise schema governance with AWS Glue & DataZone for cross-account data mesh patterns.
- π€ Shipped Shabdha β multilingual speech-to-text & AI writing assistant with RAG-augmented context, now live on the Mac App Store.
I don't just integrate LLM APIs β I design AI systems with architectural rigour:
- State-machine-enforced LLM workflows β mode separation between coaching, assessment, and harvesting prevents model drift and ensures consistent outputs
- Evidence-grounded scoring engines β every AI-generated score traces back to specific claims, rubric criteria, and JD-parsed expectations (no black-box ratings)
- Multi-model orchestration β routing different tasks to the right model (Claude for nuanced coaching, GPT for structured extraction, Whisper for transcription)
- Seniority-calibrated prompt pipelines β dynamically adjusting evaluation depth, vocabulary expectations, and scoring thresholds based on role level
- Quality gates on LLM outputs β validation layers that catch hallucination, truncation, and scoring inconsistencies before they reach the user
- Voice AI integration β end-to-end speech pipelines with VAD, barge-in handling, transcript editing, and TTS for natural conversation flow
"Architecting systems that think, learn and scale."




