Main Responsibilities
Software Engineering & Craftsmanship
- Embed Clean Code principles (e.g. SOLID, DRY, YAGNI) as non-negotiable standards across all teams.
- Own the engineering quality framework: code review standards, static analysis gates, test coverage requirements, and performance benchmarks.
- Lead by example - contribute to critical codebases, perform deep technical code reviews, and pair-program with engineers to model best practice.
- Drive Test-Driven Development (TDD) and Behaviour-Driven Development (BDD) adoption to improve correctness and documentation.
- Define and enforce Definition of Done (DoD) criteria that include architectural, security, and performance quality gates.
Software Architecture
- Design end-to-end architectures for capital markets platforms (pricing engines, order management, risk, post-trade) prioritizing low latency, fault-tolerance, and auditability.
- Define and govern technology standards, patterns, and reference architectures across the division.
- Drive architectural reviews and Architectural Decision Records (ADRs), ensuring decisions are documented, peer-reviewed, and communicated.
- Balance tactical delivery needs with long-term architectural health - managing trade-offs transparently.
- Champion event-driven, domain-driven, and cloud-native architectures where appropriate.
GenAI / Agentic AI for Software Engineering
- Integrate GenAI/Agentic AI into engineering workflows to accelerate coding, testing, documentation, and troubleshooting.
- Build reusable GenAI, MCP components, prompt libraries, engineering agents, automated test generators and code refactoring assistants.
- Partner with enterprise AI teams to ensure governance, data safeguards, and safe model usage.
- Track and report measurable productivity, quality, and cycle-time improvements enabled by GenAI.
Chapter Leadership
- Lead and grow the Engineering Chapter: a cross-filiere community of practice for software engineers across Capital Markets IT.
- Convene regular Chapter sessions, tech talks, architecture story boards, refactoring workshops, and book clubs to foster continuous learning.
- Define and maintain a shared engineering competency framework and career ladder for software engineers.
- Mentor senior and principal engineers provide structured technical coaching aligned with individual growth plans.
- Collaborate with Tribe Leads and Product Owners to ensure engineering quality does not erode under delivery pressure.
Technical Governance & Strategy
- Own the technology radar for Capital Markets IT: assess, trial, adopt or hold technologies in partnership with the global architecture and engineering teams.
- Lead the technical due diligence on vendor solutions, open-source frameworks, and cloud services.
- Track and present engineering health metrics (code quality, deployment frequency, MTTR, change failure rate) to leadership.
- Partner with Cloud, Security and infrastructure teams to embed shift-left practices into the SDLC.
Qualifications and Profile
- Master or Bachelor's degree in Computer Science/ Information Technology/ Programming & Systems Analysis/ Science (Computer Studies) faculties.
- AI Proficiency
- Demonstrated ability to effectively utilize AI-powered tools (e.g., GitHub Copilot) to enhance productivity and problem-solving capabilities.
- Understanding of AI/ML fundamentals including prompt engineering, model limitations, and best practices for human-AI collaboration.
- Experience in evaluating AI-generated outputs for accuracy, security, and alignment with business requirements.
- Ability to identify opportunities for AI integration and automation within existing workflows and processes.
Domain & Technical Background
- 10+ years of software engineering experience, with at least 4 years in a principal, staff, or architect role.
- Core: Deep hands-on expertise in at least one primary language ecosystem.
- Java / Kotlin (Spring Boot, Project Loom, GraalVM).
- Python (asyncio, Cython, NumPy/Pandas for quant workflows).
- C++ (modern C++20, lock-free structures, FPGA/kernel bypass desirable).
- Proven background in Capital Markets IT: trading systems, risk engines, order routing, or post-trade processing.
- Experience designing distributed systems with strong consistency, exactly-once semantics, and sub-millisecond latency requirements.
- Hands-on experience with messaging infrastructure: Kafka, Solace, or similar low-latency brokers.
- Cloud architecture experience (AWS, Azure, or GCP) with an understanding of hybrid cloud patterns common in regulated financial environments.
- Practical experience applying GenAI & Agentic AI tools/frameworks in enterprise engineering workflows.
Craftsmanship & Engineering Excellence
- Demonstrable commitment to Clean Code and software craftsmanship able to articulate and teach these principles.
- Experience implementing and governing CI/CD pipelines with quality gates (SonarQube, Checkmarx, Veracode, or equivalent).
- Strong understanding of software testing strategies: unit, integration, contract, performance, and chaos engineering.
- Familiarity with Domain-Driven Design (DDD), Event Sourcing, and CQRS patterns in a financial domain context.
