Senior Software Engineer – AI, ML

CFC

. Design, build and run production AI agents automating multi-step underwriting decisions over unstructured data .

Posted 11/3/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing AI agents for automated decision-making, with a strong focus on system design, cloud infrastructure management, and rigorous testing practices. Proficient in developing APIs and data services while ensuring high production standards and effective collaboration across teams.

Highest-signal resume keywords

LLM-Based Agent DevelopmentPython Software DevelopmentAsynchronous ProgrammingPostgreSQL Database ManagementInfrastructure-As-Code with Terraform

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonGoJavaC#FastAPIPostgreSQLMicroservicesRESTful APIsCI/CD WorkflowsUnit Testing

Soft Skills

Clear CommunicationPragmatic JudgementIndependent WorkingTechnical InfluenceMentoring Ability

Tools & Technologies

TerraformAzureDockerKubernetesAzure Container AppsGKEECSAzure Service BusLangGraphLangChain

Industry Keywords

AI AgentsUnderwriting DecisionsData Science CollaborationHigh-Stakes Decision-MakingInsurance

Tech Stack

Tools & technologies

AzureCloudDockerJavaKubernetesMicroservicesPostgresPythonTerraformGo

About the role

Key responsibilities & impact

Design, build and run production AI agents automating multi-step underwriting decisions over unstructured data
Build the agent runtime, including orchestration, durable state, retries and recoverable long-running workflows
Develop tools, APIs and data services with clear contracts, predictable failure modes and full auditability
Engineer guardrails, human-in-the-loop checkpoints and fallbacks for high-stakes automated decisions
Instrument, monitor and troubleshoot production agents and services, including tracing, cost, latency and decision logs
Collaborate with machine learning engineers on evaluations and improvements
Drive system design and architectural decisions for agents and surrounding services
Design and evolve data models and database schemas for submissions, agent runs, decisions and audit trails
Provision and manage cloud infrastructure using Terraform
Maintain high production standards across agent-generated code and tests
Work with business, product and engineering teams on delivery cadence, expectations and pragmatic engineering trade-offs
Support other engineers through code reviews, best-practice guidance and knowledge sharing

Requirements

What you’ll need

Hands-on experience building LLM-based agents or agentic systems in production, ideally with LangGraph, LangChain, or equivalent systems
Strong understanding of agent failure modes, including non-determinism, tool failures, runaway loops, cost and latency issues
5+ years’ professional software development experience in Python or another backend language such as Go, Java or C#
Working knowledge of Python or ability to transfer backend-language skills quickly
Strong experience with asynchronous and concurrent programming
Rigorous unit and integration testing experience
Day-to-day experience delivering software with AI coding agents
End-to-end system design experience, including service boundaries, data flows and failure modes
Strong relational database and data modelling experience
PostgreSQL experience including schema design, query performance, transactions, concurrency and safe schema migrations
Experience building distributed asynchronous microservices with message brokers such as Azure Service Bus
Understanding of at-least-once delivery, idempotency and dead-letter handling
Experience building clear, well-documented RESTful APIs
Experience with FastAPI
Strong cloud and infrastructure-as-code experience
Hands-on experience with Azure and Terraform; IaC experience is essential
Experience with Docker and production container platforms such as Azure Container Apps, Kubernetes, GKE or ECS
Experience with CI/CD workflows and YAML pipeline definitions
Clear communication, pragmatic judgement, independent working, technical influence and mentoring ability
Experience with high-stakes or regulated decision-making agents, data science collaboration, Databricks, or insurance is useful but explicitly a nice-to-have rather than a requirement

Benefits

Comp & perks

Passionate, intense work environment focused on colleagues, customers, brokers and carriers
Culture that encourages challenging existing processes and continuous improvement
Fun, inclusive workplace welcoming all viewpoints
Respectful treatment of colleagues
Permanent full-time employment