At a Glance
- Tasks: Lead a team to deliver AI-powered tools for fraud detection and digital identity.
- Company: LexisNexis Risk Solutions, a leader in data analytics and risk management.
- Benefits: Generous holiday, health benefits, wellbeing programs, and extensive learning resources.
- Other info: Join a diverse team with excellent career growth and community support initiatives.
- Why this job: Make a real impact with cutting-edge AI technology in a dynamic environment.
- Qualifications: 7+ years in engineering, with leadership experience and strong Python/Java skills.
The predicted salary is between 80000 - 100000 £ per year.
About the Business
LexisNexis Risk Solutions provides customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we ultimately help make communities safer, commerce more transparent, business decisions easier and processes more efficient.
About the role
You will lead a multidisciplinary engineering team delivering AI-powered services and tools for digital identity, fraud detection, and behavioural intelligence. The role spans technical leadership, delivery management, hands-on architecture, and coaching of engineers in a rapidly evolving AI platform environment.
Responsibilities
- Lead and grow a team of full-stack 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 and 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 – LLM tooling, MLOps, automation.
- Set and enforce DevOps and SecOps standards across the team's services and pipelines.
- Coordinate cross-team dependencies and contribute to roadmap planning.
- Support hiring, onboarding, and performance development within the team.
Requirements
- 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 — both are in active use across the team's production services.
- Experience with Snowflake/Spark/Databricks or others, CI/CD pipelines, and modern DevOps tooling.
- Solid understanding of SecOps practices and security-conscious system design.
- Demonstrable track record of taking initiative and driving work independently.
- Working knowledge of DevOps and SecOps practices deployment patterns, and security-aware engineering.
- Broad full-stack curiosity: comfortable picking up work outside your primary discipline when the problem demands it.
Preferred
- Experience building fraud, identity, risk, or security systems.
- Experience running teams using AI and LLM development tooling and automation.
- Knowledge of feature stores, model monitoring, or real-time scoring systems.
Benefits
- Generous holiday allowance with the option to buy additional days.
- Health screening, eye care vouchers and private medical benefits.
- Wellbeing programs.
- Life assurance.
- Access to a competitive contributory pension scheme.
- Save As You Earn share option scheme.
- Travel Season ticket loan.
- Electric Vehicle Scheme.
- Optional Dental Insurance.
- Maternity, paternity and shared parental leave.
- Employee Assistance Programme.
- Access to emergency care for both the elderly and children.
- RECARES days, giving you time to support the charities and causes that matter to you.
- Access to employee resource groups with dedicated time to volunteer.
- Access to extensive learning and development resources.
- Access to employee discounts scheme via Perks at Work.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Software Engineering Lead / Applied AI Engineering employer: RELX
LexisNexis Risk Solutions is an exceptional employer that prioritises employee wellbeing and professional growth, offering a generous holiday allowance, comprehensive health benefits, and extensive learning resources. Our collaborative work culture fosters innovation in AI technology while providing opportunities for team leadership and personal development, making it an ideal environment for those passionate about advancing their careers in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineering Lead / Applied AI Engineering
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at LexisNexis. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects, especially those related to AI and ML. This is your chance to demonstrate your hands-on experience and technical prowess, so make it shine!
✨Tip Number 3
Prepare for the interview like it’s the championship game! Research LexisNexis, understand their products, and be ready to discuss how your experience aligns with their mission. Practice common interview questions and think about how you can showcase your leadership skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at LexisNexis!
We think you need these skills to ace Software Engineering Lead / Applied AI Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your technical leadership and AI experience, as these are key for the Software Engineering Lead role.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for our team. Share specific examples of your past work that align with the responsibilities listed in the job description.
Showcase Your Projects:If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We love seeing hands-on experience, especially with ML-powered services and modern DevOps practices.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen on joining our team!
How to prepare for a job interview at RELX
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and Java. Brush up on your experience with ML engineering and distributed systems, as you'll likely be asked to discuss your hands-on experience deploying ML-powered services.
✨Showcase Your Leadership Skills
Since this role involves leading a multidisciplinary team, prepare examples that highlight your technical leadership and mentoring experience. Think of specific instances where you’ve successfully guided a team or driven a project forward, especially in AI or ML contexts.
✨Understand the Business Impact
LexisNexis Risk Solutions focuses on risk evaluation and operational efficiency. Be ready to discuss how your work can contribute to making communities safer and enhancing decision-making processes. This shows you understand the bigger picture and are aligned with their mission.
✨Prepare for Collaboration Questions
Expect questions about how you would partner with Product, Architecture, and ML Research teams. Have examples ready that demonstrate your ability to coordinate cross-team dependencies and contribute to roadmap planning, showcasing your collaborative spirit.
