REQUIRED TECHNICAL SKILLS
- Core Backend (Non-Negotiable)
- Java 17+ — records, sealed classes, virtual threads / Project Loom
- Spring Boot 3.x — Spring Security, Spring Data JPA/JDBC, Spring WebFlux, Spring Cloud
- Microservices architecture patterns: API Gateway, Circuit Breaker (Resilience4j), Saga, CQRS, Outbox
- RESTful API design with OpenAPI 3.x specifications as source of truth
- Agentic & AI Tooling (Non-Negotiable)
- Production experience with LLM agent orchestration frameworks: LangChain4j, Spring AI, AutoGen, CrewAI, or equivalent
- MCP (Model Context Protocol) server implementation and enterprise tool-use integration
- RAG pipeline design: document ingestion, chunking strategies, embedding models, vector database selection, retrieval tuning
- Prompt engineering for code generation, spec synthesis, test generation, and review automation at enterprise scale
- AI-assisted development tooling: GitHub Copilot, Cursor, Claude Code, or equivalent — with demonstrated productivity outcomes
- Local/private LLM deployment (Ollama, vLLM, or similar) for secure, on-premise agentic workflows in regulated environments
- Messaging, Caching & Data
- Apache Kafka: topic design, partitioning strategy, consumer groups, exactly-once semantics, Schema Registry (Avro/Protobuf)
- Redis: cache-aside, write-through, TTL strategies, pub/sub, Lua scripting, Redis Cluster
- SQL databases: SQL Server, Oracle, PostgreSQL — schema design, query optimisation, indexing
- Vector databases: pgvector, Weaviate, Qdrant, or equivalent for RAG/embedding storage
- Cloud, DevOps & CI/CD
- AWS: ECS/EKS, Lambda, RDS, ElastiCache, S3, SQS/SNS, API Gateway, CloudWatch, IAM, Secrets Manager
- Infrastructure-as-Code: AWS CDK, CloudFormation, or Terraform
- GitHub Actions CI/CD with agentic quality gates, AI-powered code analysis steps, and automated spec validation
- Docker containerisation; Kubernetes orchestration
- Security, Compliance & Banking Context
- OAuth2 / OpenID Connect: authorization code flow, PKCE, JWT validation, refresh token rotation
- Bank PII handling: masking, tokenisation, field-level encryption, audit logging
- CBUAE data residency and UAE PDPL compliance requirements
- PCI-DSS awareness: CHD scope reduction, tokenisation, secure coding for payment flows
QUALIFICATIONS & EXPERIENCE
- 10+ years of professional hands-on backend software engineering experience in production environments — mandatory
- Demonstrated, verifiable enterprise-scale Agentic SDLC / AI-DLC implementation experience — mandatory
- Experience in banking, fintech, or a similarly regulated, high-compliance domain — strongly preferred
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (or equivalent professional experience)
- AWS Certified Developer / Solutions Architect — a plus
- Proven track record of delivering complex distributed systems with high availability and measurable performance outcomes
- Observability: OpenTelemetry, Prometheus, Grafana, structured logging, distributed tracing