AI Engineering Lead for Risk Solutions Platform

LexisNexis Risk Solutions

Greater London

On-site

GBP 140,000 - 190,000

Full time

6 days ago
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Job summary

LexisNexis Risk Solutions is seeking a technical leader to guide a multidisciplinary team building AI-enhanced risk solutions and production ML services. You will shape architecture, deploy scalable platforms, and advance DevOps/SecOps practices in a secure environment.

Expect to mentor engineers, drive ML-powered product initiatives, and collaborate with Product, Architecture, and ML Research to deliver impactful features at scale.

Qualifications

  • 7+ years in backend, full-stack, ML engineering, or distributed systems.

Responsibilities

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

Skills

Leadership
Backend/Full-stack
ML Engineering
Python
Java
Distributed Systems
Mentoring

Tools

Snowflake
Spark
Databricks
CI/CD
DevOps tooling
SecOps

Job description

LexisNexis Risk Solutions is seeking a technical leader to guide a multidisciplinary team building AI-enhanced risk solutions and production ML services. You will shape architecture, deploy scalable platforms, and advance DevOps/SecOps practices in a secure environment.

Expect to mentor engineers, drive ML-powered product initiatives, and collaborate with Product, Architecture, and ML Research to deliver impactful features at scale.

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