[Hiring] Senior Machine Learning Engineer @CFC

Role Description

Insurance isn’t the first industry most engineers think of when they imagine cutting-edge AI work. That’s exactly why this role is interesting.

CFC’s Data & AI unit is building production agentic systems that automate complex underwriting decisions - not chatbots, not copilots bolted onto legacy workflows, but autonomous multi-step AI agents that reason over unstructured data, assess risk, and drive real business outcomes. We’re using frameworks like LangChain to orchestrate LLM-driven services that sit at the heart of how the business operates. The problems are genuinely hard: ambiguous inputs, high-stakes decisions, and the kind of domain complexity that makes for satisfying engineering.

We’re also fundamentally rethinking how we deliver software. We’re moving toward an agentic-first development model - using AI agents not just in what we build for the business, but in how we build it. The goal is to multiply engineering delivery by an order of magnitude: not by cutting corners or generating throwaway code, but by designing robust systems and processes that let agents handle well-defined work while engineers focus on architecture, design, and the problems that actually require human judgment. This is a deliberate, engineering-led approach. We care about code quality, testability, and maintainability - the agent-generated code meets the same standards as everything else. We expect that a successful candidate will be able to bring their expertise to help guide and refine our agentic development process as it matures - a meaningful opportunity to influence how we work as well as what we ship.

This is a Senior Machine Learning / AI Engineer role with genuine technical leadership scope. You’ll shape the architecture of AI-driven production microservices, own system design decisions, and work at the intersection of traditional software engineering and applied AI. You’ll collaborate closely with engineers, data scientists, and product managers in a team that’s small enough for your decisions to matter and ambitious enough for the work to stay interesting.

Qualifications

• Significant experience building production-grade AI agents or LLM-powered services.
• Strong Python development experience, ideally with 6+ years of professional software engineering experience.
• A track record of writing clean, maintainable and high-quality production code.
• Experience supporting business-critical systems in live production environments.
• Strong understanding of asynchronous programming, Docker, containerised deployments and modern service architectures.
• Experience designing distributed systems, asynchronous microservices and event-driven architectures.
• Confidence leading system design discussions and making pragmatic architectural trade-offs.
• Strong cloud experience, ideally within Azure.
• Experience deploying, monitoring and maintaining ML or LLM models in production.
• Familiarity with MLOps, LLMOps, evals, monitoring and lifecycle management.
• Hands-on experience orchestrating LLM workflows using frameworks such as LangChain.
• An interest in how agentic software development can improve engineering delivery without compromising code quality.
• Strong communication skills and the ability to collaborate effectively in remote or asynchronous environments.
• An ownership mindset, with the ability to work independently and contribute effectively to shared codebases.

Requirements

• Design, develop, and maintain business-critical AI agent services.
• Build tailored agent workflows and services from business requirements, using LangChain and related frameworks with reliable patterns for LLM-driven decision-making in production.
• Integrate tests and validation to improve AI agents through evals and monitoring.
• Work with software engineers and architects to lead system design and architectural decisions.
• Translate technical specifications into clean, testable, and scalable production code.
• Work closely with cross-functional teams - engineers, data scientists, product managers - to deliver features on time and to a high standard.
• Write unit and integration tests to maintain reliability and service correctness.
• Monitor, troubleshoot, and continuously improve production services.
• Produce clear, structured documentation for systems, architecture, and processes.
• Mentor junior engineers through code reviews, best-practice guidance, and knowledge sharing.

Benefits

• Love what you do: We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers.
• Challenge everything: We’re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better.
• Have fun, be good: Insurance is a serious business, but we don’t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.