Interim Lead AI Engineer

Go Fractional; Greater London; Hybrid; GBP 120,000 - 160,000; Full time

Job summary

Go Fractional in London is seeking an Interim Lead Agentic AI Engineer on a 12-month fixed-term contract to spearhead a pioneering agentic AI project for underwriting.

You'll design and ship production-grade systems, collaborate with underwriters and portfolio managers, and own evaluation, observability, and reliability from design through production. The role is senior, product-minded, and requires hands-on delivery in a fast-moving environment.

Qualifications

• Bachelor's degree in STEM or equivalent practical experience.
• Product-minded with the ability to influence product direction and vision.
• Strong understanding of agentic AI concepts: multi-agent orchestration, tool use, memory/context management, RAG, loop engineering.
• Hands-on production experience with modern agentic AI frameworks from design to production and operational support.
• Excellent software engineering fundamentals: system design, API design, testing, CI/CD, cloud-native deployment.
• Fast-moving thinker capable of autonomous work with minimal supervision.

Responsibilities

• Design, build and ship production-grade agentic AI systems for underwriting tasks end-to-end.
• Develop evaluation and observability capabilities: test harnesses, offline/online evaluation, tracing, and fallbacks.
• Collaborate with underwriters and portfolio managers to translate needs into product and technical decisions.

Skills

Agentic AI systems

Production-grade software

Multi-agent orchestration

Evaluation & observability

CI/CD & cloud deployment

API design & software architecture

Underwriting domain knowledge

Education

Bachelor's Degree in STEM

Tools

Agentic AI frameworks

Job description

Description

Where you come in?

In this role, you'll focus on a spearhead project that's pioneering agentic technology at Ki. This project represents our next bold step forward: using agentic AI to support underwriters in their real workflows, help them make better decisions, and build a more scalable underwriting capability.

As an Interim Lead Agentic AI Engineer on a 12-month fixed-term contract, you'll take on a senior, hands-on delivery role. We're looking for someone operating at a Staff or Principal level who is product-minded, enterprising, and ready to design and build. You'll work on our core product and tackle exciting engineering challenges across extraction, workflow orchestration, human-in-the-loop review, evaluation, and production reliability.

What you will be doing:

• Design, build and ship production-grade agentic AI systems that handle data-driven underwriting and portfolio management tasks end-to-end, taking accountability for delivery from design through to running in production.
• Build and evolve the project's evaluation and observability capabilities, including test harnesses, offline and online evaluations, regression suites, tracing, and fallbacks, so that safety, reliability, cost and latency are measurable and controlled in production.
• Work directly with underwriters and portfolio managers to understand their commercial needs and translate them into product and technical decisions.

Requirements

• Bachelor's Degree or higher in a STEM field, or equivalent practical experience.
• Product-minded, demonstrated experience contributing to product direction and vision.
• Strong understanding of the concepts underpinning agentic AI systems, including multi-agent orchestration, tool use, memory and context management, RAG, and harness / loop engineering. Understanding of classical ML is a plus.
• Hands-on production experience with modern agentic AI frameworks, including taking at least one agentic system from design into production and owning the operational capabilities around it, such as evaluation, observability, FinOps, failure analysis and support.
• Excellent software engineering fundamentals, including system design and software architecture, API design, testing, CI/CD, and cloud-native deployment.
• Strong judgement in a fast-moving field: able to distinguish durable capabilities from hype, reason about trade-offs under uncertainty, and justify decisions to both engineers and stakeholders.
• Ability to become productive quickly in an unfamiliar codebase and domain, working with a high degree of autonomy and minimal supervision.

Nice-to-have:

• Experience developing industrialised machine learning applications and services.
• Experience deploying AI systems in a regulated or high-consequence environment, and applying model risk or AI governance frameworks to non-deterministic systems.
• Experience taking production platform through security reviews and remediation, strengthening security controls to meet recognised standards such as SOC 2 or ISO 27001. Experience with penetration testing is a plus.
• Experience building platform products that expose reusable capabilities through well-defined APIs and interfaces, enabling multiple teams or workflows to build on top of them.
• Experience and knowledge of the insurance market, including an understanding of the Lloyd's market and specialty insurance.
• Understanding of the importance of market compliance and core regulatory requirements.
• Prior experience delivering in a contract, consulting or embedded-expert capacity, including handover to permanent teams.
• Recognised external contribution to the field, such as open-source AI tooling, publications, conference speaking.