Lead AI Platform Engineer for Agentic Systems

Hyperlayer

Greater London

On-site

GBP 120,000 - 180,000

Full time

2 days ago

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Benefits offered by this job

Performance-based bonus

25 days annual leave + birthday + ten

Critical illness and life insurance

AXA PPP Health Insurance

Cycle-to-work

Referral bonus

Workplace Nursery Scheme

Job summary

Hyperlayer is building a cutting-edge AI-driven banking platform and seeks a Principal AI Engineer to lead AI infrastructure and the agent layer. You’ll shape end-to-end AI architecture, governance, and scalability across a multi-function system.

The role combines hands-on design with strategic decisions in a security-conscious, regulated environment. You’ll lead design reviews with peers, drive production readiness, and collaborate across data, platform, and product teams to ensure reliable,

Qualifications

8+ years of experience in AI/ML or software engineering, including designing and shipping agentic systems into production, not just prototypes.
Experience architecting agent governance for high-stakes domains: guardrails, autonomy levels, kill switches, and human-in-the-loop approval
Experience with agent runtimes - sandboxing and isolation, tool invocation (e.g. Model Context Protocol), multi-agent orchestration, and reasoning-loop control
A track record of building or operating an evaluation and analytics harness for agent behaviour: trace capture, hallucination detection, and regression testing across releases
Comfort with cloud platforms (AWS mainly, GCP is a plus) and container tech (Docker, Kubernetes)
Experience designing systems that combine deterministic, rules-based processing with agent-based reasoning in the same architecture
Solid Python and SQL skills, and hands‑on experience with LLM or agent frameworks (LangChain or similar)
Understanding of identity and authorisation models extended to non‑human/agent principals - delegated authority, composite human‑plus-agent identity
A data‑driven mindset - comfortable defining the metrics that tell you whether an agent is actually working
Strong communication and collaboration skills
Curiosity and a love for experimentation, always exploring what’s next in how AI gets embedded in complex, regulated systems

Responsibilities

Design the agentic control plane for a new platform — how agents get authored, deployed, governed, run, and observed across a complex, multi-function system
Define how agents are declared and scoped: registry, authority boundaries, autonomy levels, and tool bindings, compiled into the same versioned release artefacts as everything else
Own the evaluation and analytics layer for agent behaviour: trace capture, hallucination detection, containment measurement, cost accounting, and regression tracking across releases
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
Work closely with the platform’s core architecture and engineering leads to keep the agentic layer and the rest of the system cohesive, not two products bolted together
Shape the AI architecture for a platform still being built - your early decisions will define how agents behave across the whole system for years to come.