Senior Software Engineer - AI Developer Platform & Agentic Workflows
Job Description
[Up to c. $400k Comp Package | Office-Led Working]
Role Overview
We’re representing a global quantitative trading organisation hiring a senior software engineer into its Developer Experience function to shape the internal platform behind AI-assisted software development - to turn individual experimentation with coding agents into dependable engineering infrastructure. The team is building shared workflows, integrations, execution environments and evaluation mechanisms that allow AI to participate meaningfully across the software lifecycle while remaining controlled, observable and safe.
This is fundamentally a software and platform engineering role rather than AI research or simple enterprise rollout of coding assistants. It suits someone who has built developer-facing systems at scale and wants ownership over how agentic development is introduced into an environment where engineering velocity matters, but reliability, permissions and protection of production trading systems cannot be compromised...
Role Snapshot
- Own the architecture and continued development of an internal AI developer platform supporting agent-assisted engineering across the organisation
- Bring senior-level software engineering depth, ideally gained building developer platforms, engineering infrastructure or internal tooling used by substantial technical organisations
- Evaluate and stress-test emerging coding agents and AI development tools, making evidence-led decisions around capability, reliability, integration and practical engineering value
- Build the context and integration layer connecting agents with source code, documentation, build systems, deployment tooling, operational signals and other internal services
- Develop reusable agent capabilities, tools and orchestration patterns that move teams beyond isolated prompts towards repeatable engineering workflows
- Create controlled execution models for increasingly autonomous agents, incorporating authentication, permissions, validation, human approval and complete audit trails
- Establish evaluation frameworks using regression testing, representative datasets and production telemetry to measure output quality, reliability and impact on developer productivity
- Design shared mechanisms through which engineers can discover, reuse and improve agent workflows, prompts, skills, tools and supporting components
- Understand the software lifecycle end to end, including local development, source control, review, testing, CI/CD, deployment and production operations
- Work directly with engineering teams to identify valuable use cases, remove adoption friction, improve working practices and convert successful experiments into platform capabilities
...
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