Senior AI Engineer

axiscapital; Greater London; On-site; GBP 110,000 - 140,000; Full time

Job summary

AXIS Capital in London seeks a Senior AI Platform Engineer to design, build, and operate cloud-native AI workloads on Azure and Databricks, delivering secure and reusable capabilities across underwriting, claims, and operations.

You will own CI/CD for AI/data workloads, implement Terraform-based IaC, mentor engineers, and collaborate with cross-functional teams to advance the platform strategy and production readiness.

Qualifications

• Strong production-grade Python engineering experience.
• Experience with PySpark or large-scale data processing.
• Hands-on experience designing and operating CI/CD pipelines using Azure DevOps.
• Experience deploying workloads on Azure including identity, access control, networking and secure resource configuration.
• Practical experience with infrastructure-as-code, preferably Terraform.
• Experience building scalable AI services.

Responsibilities

• Design, build, and operate production-grade AI services, data pipelines, and platform capabilities on Azure and Databricks.
• Develop LLM-powered and agentic workflows for automation and decision support.
• Expose AI capabilities via secure APIs and backend services (e.g., FastAPI).
• Own CI/CD delivery pipelines for AI and data workloads.
• Implement infrastructure-as-code using Terraform and Azure tooling.
• Build and manage Databricks jobs, workflows, and data pipelines.
• Implement monitoring, logging, tracing, and alerting with observability tools.
• Support production AI systems including incident response and runbooks.
• Contribute to architecture decisions, engineering standards, and platform strategy.
• Collaborate with engineering, data science, product, security, and infrastructure teams.
• Mentor engineers and promote strong engineering practices.

Skills

Python engineering

PySpark

CI/CD pipelines

Azure deployments

Infrastructure-as-code

Databricks

LLM workflows

AI platforms

Tools

Terraform

Azure DevOps

Databricks

OpenTelemetry

Job description

This is your opportunity to join AXIS Capital - a trusted global provider of specialty lines insurance and reinsurance. We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture. As a member of AXIS, you join a team that is among the best in the industry.

At AXIS, we believe that we are only as strong as our people. We strive to create an inclusive and welcoming culture where employees of all backgrounds and from all walks of life feel comfortable and empowered to be themselves. This means that we bring our whole selves to work.

All qualified applicants will receive consideration for employment without regard to any protected characteristic, including age, color, disability, ethnicity, gender identity, marital status, national origin, pregnancy, race, religion, sex, sexual orientation, veteran status, or any basis prohibited by the laws that govern its operations.

Job Description: Senior AI Platform Engineer

How does this role contribute to our collective success?

The Senior AI Platform Engineer will help AXIS deliver secure, reliable, and reusable AI capabilities that support business teams across underwriting, claims, operations, and other strategic functions. This role sits at the intersection of platform engineering, DevOps, data engineering, and applied AI, with a focus on productionising AI services safely and consistently.

You will design, build, deploy, and operate cloud-native AI workloads, including LLM-powered services, agentic workflows, data pipelines, and reusable platform components. You will play a key role in improving engineering standards, automation, observability, release discipline, and operational readiness across AXIS AI platforms.

This is a hands-on senior engineering role for someone who can take ownership from design through production support, work effectively with distributed teams, and help shape pragmatic, maintainable approaches to enterprise AI delivery.

What will you do in this role?

• Design, build, and operate production-grade AI services, data pipelines, and platform capabilities on Azure and Databricks.
• Develop LLM-powered and agentic workflows that support business process automation, document intelligence, orchestration, and decision support.
• Expose AI capabilities through secure, maintainable APIs and Azure Function or Container App backend services, including FastAPI-based or other services where appropriate.
• Own CI/CD delivery pipelines for AI and data workloads, including build, release, deployment, validation, and environment promotion.
• Implement infrastructure-as-code using Terraform and Azure-native tooling, ensuring environments are repeatable, secure, and supportable.
• Build and manage Databricks jobs, workflows, asset bundles, and data engineering pipelines.
• Implement monitoring, logging, tracing, and alerting using OpenTelemetry or equivalent observability tools.
• Support production AI systems, including incident response, troubleshooting, operational runbooks, release readiness, and service improvement.
• Contribute to architecture decisions, engineering standards, reusable patterns, and platform strategy.
• Collaborate with engineering, data science, product, security, infrastructure, and business teams to deliver end-to-end solutions.
• Mentor engineers, lead technical enablement sessions, and promote strong engineering practices across the team.

What will you need to succeed?

Required skills and experience

• Strong production-level Python engineering experience, with the ability to build maintainable, tested, and supportable services.
• Experience with PySpark or equivalent large-scale data processing frameworks.
• Hands‑on experience designing and operating CI/CD pipelines using Azure DevOps or similar tooling.
• Experience deploying and supporting workloads on Azure, including identity, access control, networking and secure resource configuration.
• Practical experience with infrastructure‑as‑code, preferably Terraform.
• Experience building… from service for coverage? (Truncated)

Desirable skills and experience

• Experience with Databricks Jobs, Workflows, Asset Bundles, Apps, and medallion-style data architectures.
• Experience with Azure AI Foundry, Azure OpenAI, LLM-based application development, or agent SDKs and frameworks.
• Experience with MLflow, model lifecycle management, evaluation, tracing, and AI observability.
• Experience with conta