TradingStandard
2025 – Present
TradingStandard B2B SaaS Platform
Founding Product Engineer architecting a component-driven B2B SaaS platform and AI-native products using Next.js, Python, and agentic AI — nominated for 'Best AI Solution for Financial Services'.
TradingStandard — Founding Product Engineer
As a Founding Product Engineer at TradingStandard (London), I architect the company’s core B2B SaaS platform from the ground up, combining full-stack engineering with AI-native product development using Python and agentic AI.
Key Achievements
- Full-Stack Architecture: Architected a component-driven B2B SaaS platform using Next.js and React, enabling rapid feature iteration and reducing time-to-market for critical user flows
- AI-Native Product Engineering: Built an agentic AI system using Python, PydanticAI, and FastAPI — engineering a domain-specific “AI Teacher” agent with vector embeddings (RAG) to optimize user trading workflows. Nominated for “Best AI Solution for Financial Services”
- AI Observability: Integrated Arize Phoenix for LLM observability, enabling real-time tracing, evaluation, and performance monitoring of AI agents in production
- DevOps: Implemented CI/CD pipelines via GitHub Actions and provisioned containerized cloud infrastructure, enabling a rapid go-to-market strategy that secured the first paying client within one month
Technologies
- Frontend: Next.js, React, TypeScript
- Backend & AI: Python, FastAPI, PydanticAI, Vercel AI SDK
- AI/ML: RAG (Vector Embeddings), Agentic AI, Arize Phoenix (LLM Observability)
- Infrastructure: GitHub Actions, Docker, Kubernetes, AWS / GCP
- Data: PostgreSQL