AI Enablement - Data Engineer

AI Enablement - Data Engineer

Embark on a transformative journey as a GenAI Engineer – Copilot Studio developer at Barclays. Our vision is to redefine the future of banking by responsibly harnessing data and Generative AI to deliver innovative, scalable, and trusted solutions across Markets and Investment Banking.

To be a successful "AI Enablement - Data Engineer" you will develop and deliver enterprise‑grade GenAI data platforms, with a strong emphasis on Copilot Studio and Power Platform. You will own and ship Studio Agents and workflows, including using Power Automate, Studio, AI Builder, Power Apps and MCP orchestration, while embedding governance, controls, and quality from day one.

You may be assessed on the key critical skills relevant for success in role, such as you will design and scale AI agent capabilities across MS Power Platform leveraging Microsoft 365 Copilot and Copilot Studio, and integrating leading OpenAI LLMs with privacy, security, and regulatory controls built in. You will work closely with bankers, product partners, technology teams, and senior stakeholders to translate business problems into production‑grade GenAI capabilities.

Basic/ Essential Qualifications:

• Ability to design, build, test, and publish custom Copilot agents using Copilot Studio, including topic design, trigger phrases, generative answers, and multi‑turn conversations
• Strong skills in prompt engineering, intent recognition, entity extraction, and conversation flow design
• Designing automated workflows triggered by Copilot agents to perform actions across enterprise systems (approvals, data updates, notifications)
• Ability to integrate agents with Power Apps (canvas or model‑driven) and line‑of‑business applications
• Partner with business, product, engineering, and data science teams to identify high‑impact GenAI use cases and translate them into production‑grade solutions.

Desirable skillsets/ good to have:

• Experience designing and overseeing GenAI and ML data pipelines, integrating structured and unstructured data for model deployment and evaluation using RAG pipelines
• Exposure to Power Platform AI Builder for text extraction, classification, and document understanding
• Experience partnering with business and engineering teams to deliver production‑grade GenAI solutions.
• Experience setting standards and best practices across data, analytics, and AI teams.
• Experience working directly with bankers or business users to translate requirements into technical deliverables.
• Ability to operate effectively in global teams across regions (US, UK, India).
• Degree in quantitative or technical discipline (Computer Science, Engineering, Mathematics, Statistics).
• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
• Exposure to retrieval‑augmented generation (RAG), agent‑based systems, and prompt engineering best practices.
• Familiarity with CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
• Strong working knowledge of Git and collaborative development workflows.
• Understanding of model risk management, explainability, and governance in regulated environments.
• Prior experience delivering AI solutions in Investment Banking or Capital Markets.

This role will be based out of Gurugram.