Job Description

Role Responsibilities

• Partner with product owners, BAs, and risk stakeholders to translate requirements into well-architected, AI-assisted solutions

• Design and operate scalable data pipelines - ingestion, transformation, enrichment, and orchestration from real-time and batch sources

• Develop cloud-native, event-driven services using serverless compute (AWS Lambda / Azure Functions) and orchestration (Step Functions / state machines)

• Write production-quality Python (and .NET where appropriate) using AI coding agents (Kiro, Claude Code, Amazon Q) while maintaining engineering rigour

• Implement AI-augmented SDLC workflows - code generation, test creation, documentation, and code review acceleration

• Build comprehensive automated test suites (unit, integration, contract) using TDD and AI-assisted generation

• Design data models, API contracts, and integration patterns for distributed systems (Solace, Kafka)

• Establish CI/CD pipelines, infrastructure-as-code, and deployment automation

• Maintain living technical documentation - ADRs, runbooks, API specs - using AI tooling

• Mentor junior engineers in AI-assisted development and prompt engineering

• Perform performance profiling and capacity planning for latency-sensitive risk workloads

• Champion TP ICAP engineering standards, AI governance guardrails, and best practices

Required Experience

Technical

• 7+ years hands-on Python - production services, data engineering, risk calculation workloads

• Proven data pipeline experience - ingestion, transformation, enrichment, orchestration

• Serverless event-driven solutions - AWS Lambda / Azure Functions, Step Functions, retry/failure handling

• Cloud platforms (AWS or Azure) - compute, storage, managed databases, messaging, monitoring

• Event-driven architectures - Solace, Kafka/MSK, SQS, async processing patterns

• Relational databases (PostgreSQL, Oracle) - schema design, query optimisation, data modelling

• Software design fundamentals - OOD, SOLID, distributed patterns (CQRS, saga, circuit breaker)

• Git-based workflows, trunk-based development, CI/CD automation (GitLab CI, GitHub Actions)

• Clean, testable, well-documented code for large-scale production systems with rapid release cadence

• C# / .NET working knowledge useful but not primary focus

AI-Enabled Development (required)

• Daily hands-on use of AI coding agents (Claude Code, GitHub Copilot, Amazon Q, Kiro) - not just experimentation

• Prompt engineering for code generation, refactoring, and test creation

• Ability to critically evaluate AI-generated code for correctness, security, and maintainability

• Integrating AI agents into the SDLC - from requirements through testing and documentation

Soft Skills

• Self-starter - works independently to achieve results

• Performs well under pressure - flexible, positive, and focused during change

• Strong communication with internal and external stakeholders

• Agile experience (Scrum, SAFe, Kanban)

• Excellent attention to detail, highly organised, proactive

Desirable Experience

• High-throughput ETL / data-processing pipelines

• Infrastructure-as-code (CloudFormation, Terraform)

• Containerisation (Docker, ECS/EKS, AKS)

• Refactoring monoliths to microservices

• C# / .NET (6/7/8) and ASP.NET Core

• React or Angular, TypeScript/JavaScript

• XML/BML/fpML and financial messaging formats

• Risk, settlement systems, or trading organisations

• Data modelling