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AI Engineer - Agentic Coding

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Hyperlayer
Full Time position
Listed on 2026-09-01
Job specializations:
  • Software Development
    DevOps, Software Engineer, Backend Developer, Software Architect
Salary/Wage Range or Industry Benchmark: 120000 - 190000 GBP Yearly GBP 120000.00 190000.00 YEAR
Job Description & How to Apply Below
Position: Staff AI Engineer - Agentic Coding
Location: Greater London

About Hyperlayer

Hyperlayer is the intelligent banking platform built for the agentic economy: the financial control layer that sits above banks' existing cores, enabling next-generation Smart Accounts, without ripping anything out. From a single integration, we give financial institutions a secure rules and orchestration engine that lets them design, launch and scale hyper-personalised products in weeks while preserving stability, compliance and control. And there's nothing like us anywhere in the world.

About

Hyperlayer

Hyperlayer is the intelligent banking platform built for the agentic economy: the financial control layer that sits above banks' existing cores, enabling next-generation Smart Accounts, without ripping anything out. From a single integration, we give financial institutions a secure rules and orchestration engine that lets them design, launch and scale hyper-personalised products in weeks while preserving stability, compliance and control. And there's nothing like us anywhere in the world.

Hyperlayer works with Tier 1 and Tier 2 FIs across the UK, US, EMEA and Hong Kong, with an award-winning UK consumer app (Hyper Jar) sitting in the group. We're creating the fintech category that every bank in the world needs: programmable, governed, agent-ready accounts. Your job is to make sure our audiences know that.

We’re Growing Our AI Team

Hyperlayer is on a mission to reinvent how people and businesses move money, and we need a Principal AI Engineer with big ideas to help us make it happen. This isn’t just about writing code; it’s about building the AI infrastructure for the future of payments.

You’ll take the lead on how our engineers actually build software — treating the tools they use to ship code as products in their own right, with a real user experience worth measuring and improving. If you’re excited about reshaping how engineering teams work day to day, you’ll fit right in.

What You'll Do
  • Define and evolve how our engineering team builds software with AI coding agents — from initial spec through to review, deployment, and monitoring
  • Horizon-scan and benchmark emerging open-source coding harnesses and open-weight models, and lead their introduction with enterprise-grade controls — security review, access management, and audit trails
  • Extend AI-assisted development into QA and Dev Ops: automated test generation, code review, CI/CD, deployment, and production monitoring
  • Build the feedback loop for our coding agents - capturing engineer satisfaction and outcomes per session, then using that data to improve the tools, prompts, and rules we ship
  • Own the steering rules, prompts, and guardrails that shape how coding agents behave across the engineering team, keeping humans in the loop on the decisions that matter
  • Evaluate and select AI coding tools and frameworks, and build the internal benchmarks that back those calls
  • Participate in system level design and architecture decisions with your peers
  • Make sure our AI systems scale, stay reliable, remain secure, and meet financial regulation objectives
  • Mentor engineers as they adapt to a new way of building software, sharing what’s working and what isn’t
  • Shape the future of engineering at Hyperlayer - your approach to how we build will influence the roadmap.
Qualifications
  • 8+ years’ experience in software engineering, including recent hands‑on work adopting AI coding agents into a real engineering workflow
  • Experience designing structured, spec‑driven or workflow‑driven processes for AI‑assisted development — requirements, planning, implementation, and review
  • A track record of building internal tooling, evaluation frameworks, or benchmarks to measure and improve engineering productivity or developer experience
  • Experience benchmarking open‑source tools or open‑weight models against proprietary alternatives, and assessing them for safe enterprise adoption
  • Comfort with cloud platforms (AWS mainly, GCP is a plus) and container tech (Docker, Kubernetes)
  • Experience extending AI‑assisted workflows into QA and Dev Ops: automated testing, code review, CI/CD, deployment, and monitoring
  • Solid Python skills, and comfort defining the rules, prompts, and guardrails that…
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