Data Automation & AI Engineer
AI in this role
Purpose of the role
To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.
Accountabilities
- Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.
- Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.
- Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
- Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth.
- Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
- Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.
Analyst Expectations
- To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
- Requires in-depth technical knowledge and experience in their assigned area of expertise
- Thorough understanding of the underlying principles and concepts within the area of expertise
- They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
- 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 develop technical expertise in work area, acting as an advisor where appropriate.
- Will have an impact on the work of related teams within the area.
- Partner with other functions and business areas.
- Takes responsibility for end results of a team’s operational processing and activities.
- Escalate breaches of policies / procedure appropriately.
- Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
- Advise and influence decision making within own area of expertise.
- Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
- Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
- Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
- Make evaluative judgements based on the analysis of factual information, paying attention to detail.
- Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
- Guide and persuade team members and communicate complex / sensitive information.
- Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.
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.
Join us as a Data Automation & AI Engineer at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.
You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.
To be successful as a Data Automation & AI Engineer, you should have experience with:
Essential Skills:
- Proficient in programming skills in Python and Agentic Workflows
- Experience to Generative AI concepts, including prompt engineering or frameworks like LangChain.
- Good understanding of machine learning concepts, automation, and exposure to libraries such as scikit-learn, TensorFlow, or PyTorch.
- Experience with Git-based version control systems (e.g., GitHub, GitLab).
- Good understanding of CI/CD concepts (e.g., Jenkins or GitHub Actions).
- Good knowledge of API development and integration concepts.
- Exposure to cloud platforms (preferably AWS – RDS, EKS, EC2, Lambda or similar services).
- Good understanding of containerization concepts (Docker preferred).
- Experience with AI/ML lifecycle concepts, including model development, training, and deployment
Some other highly valued skills include:
- Exposure to data processing tools or platforms such as Snowflake, Databricks, or basic SQL.
- Familiarity with data engineering concepts (e.g., ETL pipelines, Airflow, or Spark basics).
- Awareness of Responsible AI principles, model interpretability, and governance fundamentals.
- Understanding of DevOps fundamentals and software delivery pipelines.
- Strong problem-solving mindset and eagerness to learn new technologies.
- Good communication and collaboration skills.
- Experience and good understanding of software engineering principles such as modular design, code readability, and testing.
This role is based out of Pune.
How we score this
Data Automation & AI Engineer at Barclays scores 21 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What's a project where you used LangChain hands-on?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, AI Agents, AI Safety, LangChain, and PyTorch. 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.
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