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002 — Stack

Technical Stack

11 domains · Production-proven across 8 sectors Java · AWS · AI Engineering · DevSecOps
01 — Java & Spring Ecosystem

The primary toolchain — production-hardened over 25 years. Java 21 modern features (virtual threads, records, sealed classes, pattern matching) with Spring Boot 3.x across every layer.

Java 21 Spring Boot 3.x Spring Cloud Spring Security 6 Virtual Threads Records Sealed Classes Pattern Matching Spring WebFlux Spring Batch 5 Spring Cloud Gateway Spring Data Spring Actuator MapStruct Maven Gradle
02 — Architecture & Design Patterns

Patterns applied where they genuinely reduce complexity — hexagonal for testability, DDD for domain fidelity, CQRS and event sourcing for audit and scalability.

Hexagonal Architecture Domain-Driven Design CQRS Event Sourcing Saga Pattern Outbox Pattern Strangler Fig Clean Architecture 12-Factor App API-First Design OpenAPI / Swagger Microservices
03 — Trading & Exchange Systems

Specialist depth across all major betting exchanges — real-time market data, algorithmic strategy infrastructure, risk controls, and in-play execution at low latency.

Betfair Exchange API Betfair Streaming API TA4J Betdaq Smarkets Matchbook Order Book Modelling Price Velocity Weight of Money In-Play Automation Risk Management BSP / Starting Price Backtesting Frameworks
04 — Event-Driven & Messaging

Asynchronous architectures for real-time pipelines, trading feeds, and decoupled distributed systems — designed for exactly-once correctness and replay capability.

Apache Kafka AWS SNS / SQS Spring Cloud Stream Kafka Streams Exactly-Once Semantics Transactional Outbox Spring Kafka RabbitMQ WebSockets SSE Dead Letter Queues
05 — Cloud & AWS

AWS-native design using CDK v2 as the IaC backbone — serverless-first where it fits, ECS Fargate for long-running services, with SnapStart and GraalVM Native for cold-start-sensitive workloads.

AWS CDK v2 AWS Lambda ECS Fargate API Gateway S3 SQS / SNS RDS (PostgreSQL) DynamoDB Secrets Manager CloudWatch CloudFormation SnapStart GraalVM Native Blue-Green Deployment
06 — DevOps & Platform

Infrastructure as code, automated CI/CD pipelines, and zero-downtime deployments across containerised Linux environments — from commit to production.

Docker Kubernetes GitHub Actions Jenkins Ansible Terraform Helm Bash Linux Zero-Downtime Deployment Graceful Shutdown ArgoCD
07 — Data & Persistence

Relational, document, cache, and time-series — chosen for the problem, not the trend. Schema migration and distributed scheduling handled as first-class concerns.

PostgreSQL MongoDB Redis DynamoDB MS SQL Server MySQL Hibernate / JPA Spring Data JPA Spring Data MongoDB Flyway ShedLock Keyset Pagination Apache Druid
08 — Testing & Quality Engineering

Test-first by default — from unit through mutation and property-based testing. Contract testing across service boundaries. Quality engineered in, not inspected in.

TDD Testcontainers BDD / Cucumber JUnit 5 Mockito AssertJ WireMock Spring Cloud Contract PiTest (Mutation) jqwik (Property-Based) Spring WebMvcTest k6 / Load Testing
09 — Security & Observability (DevSecOps)

Security embedded throughout the pipeline — not bolted on at the end. Runtime visibility, circuit-breaking, and compliance controls across every service in production.

Spring Security JWT / OAuth2 / OIDC Micrometer AWS IAM Secrets Manager / KMS OWASP Top 10 SAST / DAST Snyk Prometheus Grafana Zipkin / Jaeger ELK Stack Resilience4j HikariCP Monitoring
10 — AI-Assisted Engineering

AI integrated across the full engineering lifecycle — from rapid prototyping and strategy modelling to automated test generation and production-grade code delivery. Used to compress design-to-deployment cycles without compromising quality or correctness.

Claude Code GitHub Copilot Claude API (Anthropic) GPT-4o Cursor Prompt Engineering AI Test Generation AI Code Review LLM Strategy Modelling AI Backtesting Analysis RAG Pipelines LangChain4j Rapid Prototyping AI-Driven Refactoring
11 — Full Stack & Languages

Backend-primary with real full-stack reach — Python for data modelling, ML, and scripting; TypeScript and React for frontend integration; growing capability across the whole delivery stack.

Python TypeScript React pandas NumPy scikit-learn Jupyter JavaScript HTML / CSS SQL Bash Gradle DSL REST / OpenAPI GraphQL

See how this stack is applied in real projects.