Senior AI Engineer
Barclays is hiring a Senior AI Engineer. Level rates it ; you can apply on Barclays.
Level's read on this job
- Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
- The posting mentions Anthropic, LangChain and LangGraph among its tools and skills.
- Level classes it as a senior role.
- Barclays has 679 other open roles on Level.
- Posted in the last few days.
AI in this role
Design, develop, and operationalize machine learning models and analytics solutions as a senior AI engineer.
Purpose of the role
To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making
Accountabilities
- Design analytics and modelling solutions to complex business problems using domain expertise.
- Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
- Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
- Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
- Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
- Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy.
- Ensure all development activities are undertaken within the defined control environment.
Vice President Expectations
- To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
- If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
- If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others..
- OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
- Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
- Manage and mitigate risks through assessment, in support of the control and governance agenda.
- Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
- Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
- Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
- Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
- Adopt and include the outcomes of extensive research in problem solving processes.
- Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
We are seeking a highly skilled Senior AI Engineer at Barclays, to design and build advanced machine learning and AI solutions that enhance our ability to detect financial crime, prevent fraud, and safeguard our customers.
Working closely with data scientists and engineers, you will focus on developing scalable ML pipelines, agentic AI systems, production-grade model code, and robust monitoring systems. You will play a key role across the full AI/ML lifecycle—from initial concept and data exploration through to deployment—while ensuring adherence to strict governance, documentation, and regulatory standards.
To be successful as a Senior AI Engineer, you must have the following essential skills:
- Extensive experience developing scalable, modular, and maintainable Python applications
- Experience deploying observable, well-tested, robust Generative AI applications at scale, including with relevant frameworks (e.g., LangGraph/LangChain, Strands SDK, Anthropic SDK, AWS Bedrock, CrewAI).
- Experience in machine learning development (training, evaluating, deploying, and monitoring models at scale).
- Experience with deep learning/NLP frameworks (e.g., PyTorch, Hugging Face).
- Solid understanding of software engineering principles, design patterns and ML lifecycle practices (MLOps/LLMOps).
- Previous experience of owning and delivering AI and ML projects, including stakeholder management.
Some other highly valued skills may include:
- Experience leading machine learning engineering or development teams.
- Experience with cloud platforms (AWS, Azure, GCP) or ML platforms (e.g., Databricks).
- Experience with evaluating LLM-based applications including AI-as-a-judge.
- Experience demonstrating Generative AI skills such as retrieval-augmented generation, fine-tuning, prompt-engineering.
- Exposure to distributed data processing frameworks (e.g., Spark).
- Exposure to fraud detection, anti-money laundering, anomaly detection, or graph/network-based modelling.
- Understanding of model risk management, governance, and regulatory controls in financial services.
You may be assessed on the key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
This role will be located at our London office, with a hybrid working model of working a minimum of 3 days per week in the office.
How we rate this
Senior AI Engineer at Barclays rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $182k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, ML Ops, NLP, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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