The Department
Developer Engineering is a function of the CTO organization. Our mission is to make it easy and enjoyable for software engineering teams to go from a business idea to delivering an innovative product solution. We are committed to modernizing our toolchain, streamlining delivery processes, automating at scale , and embedding intelligent controls that help engineering teams ship with confidence and speed.
The Team
Within the Developer Engineering department, the Developer Services group is a dedicated expert team at the forefront of the everything-as-code agenda. We exist to deliver measurable reductions in process friction, manual effort, and human error — ensuring our policies, standards, and controls are codified, automated, and consistently applied across the organization.
We hold a unique mandate as part of a greenfield program to shape critical technical consensus at global scale , transforming how the firm's engineers build and apply controls across its technology landscape.
Developer Services is a cross-functional team of engineers, AI practitioners , data scientists, business analysts, and product managers — working together to engineer next-generation codified controls , build the platforms that power them, and drive enterprise adoption .
The Opportunity
This is a rare greenfield / build-from-scratch opportunity to create an enterprise agentic AI capability — the agent orchestration layer , the guardrails , and the adoption model — inside one of the world's most highly regulated financial environments .
As the Agentic AI Engineering Lead , you will own the enterprise rollout of autonomous and semi-autonomous AI agents across the software delivery lifecycle: designing the multi-agent orchestration platform that plans, routes, executes, and audits agent work, and defining the control model that makes AI autonomy safe under financial services regulation . You will start from a blank page, set the technical strategy , lead a team of engineers , and partner with product, security , risk , controls , and platform teams to take agents from pilot to firm-wide production .
You will work hands-on with frontier Generative AI technologies — large language models (LLMs) such as GPT , Gemini , and Claude — through prompt engineering , context engineering , tool / function calling , retrieval-augmented generation (RAG) , agentic planning loops , and evaluation harnesses that prove agent behaviour before production.
This is not just an engineering role. It is a leadership opportunity to define how agentic AI is built, governed, and scaled across a global bank .
Responsibilities
Agentic AI Platform & Agent Orchestration (Build from Scratch)
Architect and build the enterprise agent orchestration platform from the ground up: agent runtime , planner/executor loops , tool and MCP-style integration layer , memory and context management , state persistence , and human-in-the-loop checkpoints
Design multi-agent patterns — supervisor/worker hierarchies , task decomposition , delegation , hand-off , and recovery — with deterministic fallbacks where autonomy is not appropriate
Build the tool integration surface that lets agents act safely on real enterprise systems: source control, CI/CD , ticketing, service catalogues, data platforms, and internal APIs , each with scoped, least-privilege credentials
Define the evaluation and observability layer: golden datasets , offline and online evals , regression gates on agent behaviour , prompt and model version control , token and cost governance , and end-to-end tracing of every agent decision and action
Establish reusable agent patterns, SDKs, and templates so other engineering teams can build compliant agents without rebuilding the plumbing
Enterprise Rollout & Adoption
Own the enterprise rollout strategy : define the autonomy maturity ladder (assisted → supervised → autonomous), promotion criteria between stages, and the team onboarding path
Prioritize and land high-value agentic use…