Engineering Lead, AI-Driven Risk Platforms

LexisNexis Risk Solutions; England; On-site; GBP 120,000 - 180,000; Full time

Job summary

LexisNexis Risk Solutions is seeking a technical leader to guide a multidisciplinary team building AI-enhanced products, internal tools, and platform capabilities at scale. You will blend hands-on engineering with people leadership to deliver scalable machine learning services.

You will partner with Product, Architecture and ML Research to drive architecture, deployment pipelines, and secure, reliable operations across production systems.

Qualifications

• 7+ years in backend, full-stack, ML engineering, or distributed systems.
• 2+ years in technical leadership, team leadership, or senior mentoring roles.
• Hands-on experience deploying ML-powered services into production.
• Strong Python and Java, across production services.
• Experience with Snowflake, Spark, Databricks or similar technologies, CI/CD pipelines, and modern DevOps tooling.
• Solid understanding of SecOps practices and security-conscious design.

Responsibilities

• Lead and grow a team of backend/ML engineers and a UI developer.
• Define technical direction for AI-enhanced services and platform components.
• Drive architecture for model deployment pipelines, inference APIs, and data/feature systems.
• Ensure high-quality delivery across code quality, testing, docs, and observability.
• Partner with Product, Architecture, and ML Research teams to prioritise and scope work.
• Foster modern AI development practices including MLOps and automation.
• Set and enforce DevOps and SecOps standards across services and pipelines.
• Coordinate cross-team dependencies and contribute to roadmap planning.

Skills

Backend

Full-stack

ML Engineering

Distributed Systems

Tools

Python

Java

Job description

LexisNexis Risk Solutions is seeking a technical leader to guide a multidisciplinary team building AI-enhanced products, internal tools, and platform capabilities at scale. You will blend hands-on engineering with people leadership to deliver scalable machine learning services.

You will partner with Product, Architecture and ML Research to drive architecture, deployment pipelines, and secure, reliable operations across production systems.