At a Glance
- Tasks: Lead a team to develop AI-powered tools for digital identity and fraud detection.
- Company: Join LexisNexis Risk Solutions, a leader in data analytics and risk management.
- Benefits: Enjoy generous holidays, health benefits, and extensive learning resources.
- Other info: Be part of a culture that values innovation and community support.
- Why this job: Make a real impact with cutting-edge technology in a dynamic environment.
- Qualifications: 7+ years in engineering, with strong leadership and ML experience.
The predicted salary is between 80000 - 100000 £ per year.
Would you enjoy working on our cutting-edge products? Are you ready for a lead Engineer role?
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 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.
- 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: LexisNexis Risk Solutions
LexisNexis Risk Solutions is an exceptional employer, offering a dynamic work environment where innovation meets purpose. With a strong focus on employee growth and well-being, we provide generous benefits, including a competitive pension scheme, extensive learning resources, and opportunities for community engagement through RECARES days. Join us in our mission to enhance operational efficiency and make communities safer while leading a talented team in a cutting-edge AI platform environment.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineering Lead / Applied AI Engineering
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and ML. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨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, we love seeing candidates who are proactive!
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 leadership experience and technical expertise in AI and ML, as these are key for us at LexisNexis Risk Solutions.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about leading a team in AI engineering. Share specific examples of your past achievements and how they relate to the role, showing us your personality and enthusiasm.
Showcase Your Technical Skills:Don’t shy away from detailing your hands-on experience with Python, Java, and any relevant tools like Snowflake or Databricks. We want to see how you’ve applied these skills in real-world scenarios, especially in deploying ML services.
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 gives you a chance to explore more about our company culture!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Tech Inside Out
Make sure you brush up on your Python and Java skills, as these are actively used in the team's production services. Be ready to discuss your hands-on experience with deploying ML-powered services and how you've tackled challenges in that area.
✨Showcase Your Leadership Skills
As a Software Engineering Lead, you'll need to demonstrate your technical leadership and mentoring abilities. Prepare examples of how you've led teams, defined technical direction, and fostered a culture of modern AI development practices in your previous roles.
✨Understand the Business Context
Familiarise yourself with LexisNexis Risk Solutions and their focus on risk evaluation and operational efficiency. Be prepared to discuss how your engineering expertise can contribute to their mission of making communities safer and business decisions easier.
✨Prepare for Cross-Team Collaboration
Since the role involves partnering with Product, Architecture, and ML Research teams, think about how you've successfully coordinated cross-team dependencies in the past. Have specific examples ready that highlight your communication and collaboration skills.
