Chapter Lead AI & Architect

Position

We are looking for an exceptional Software Architect and Engineering Chapter Lead to shape the technical culture and engineering excellence of the IT division. This position will be the guardian of software craftsmanship, ensuring that every system we build is clean, resilient, observable, and built to last. Beyond your individual architectural contributions, you will animate our Engineering Chapter: a community of practice that elevates every engineer on the floor through mentorship, standards, and a relentless pursuit of quality.

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 practices.
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), prioritising 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 storyboards, 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’s or Bachelor’s degree in Computer Science, Information Technology, Programming & Systems Analysis, or 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.