Michał Milewski

Directed automation-focused platforms and AI-enhanced services, owning backend architecture, real-time dashboards, and engineering standards. Engineered 7+ Django REST microservices and real-time Next.js dashboards, accelerating automation workflow speed and responsiveness. Delivered AI-integrated features, including Model Context Protocol (MCP) endpoints and internal automation agents, reducing manual operations across multiple teams. Architected modular APIs backed by PostgreSQL, Redis, and RabbitMQ, enabling fault-tolerant task pipelines handling thousands of events/day. Introduced WebSocket-based dashboards enabling low-latency data updates and smoother user interactions. Deployed monitoring and profiling tools that improved incident detection and reduced recovery time. Guided junior developers and led code reviews; standardized test suites (pytest + Jest), increasing coverage from ~45% to 80%.

Strengthened high-performance GraphQL platforms across distributed internal systems. Constructed scalable GraphQL services powering analytics and customer intelligence platforms. Crafted type-safe schemas and optimized resolvers with dataloaders to cut query latency significantly. Rolled out a federated GraphQL architecture unifying authentication, analytics, and billing services. Enhanced responsiveness using PostgreSQL storage and Redis-based caching layers. Produced CI/CD pipelines in GitHub Actions for schema validation, versioning, and automated testing.

Built secure ML-powered microservices for financial fraud detection and compliance automation. Developed FastAPI/Flask microservices for real-time fraud detection pipelines backed by TensorFlow inference services. Incorporated LangChain + Pinecone-based RAG enrichment to deliver context-aware scoring and minimize false positives. Published internal APIs and utilities exposing model outputs, anomaly signals, and risk insights to analyst-facing tools. Shaped schemas, data contracts, and feature interfaces in partnership with data engineering groups. Launched services on AWS ECS, with full IAM, VPC, autoscaling, and monitoring for regulated environments. Ensured compliance with audit/logging standards and data-governance requirements.