WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence. We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 66,000+ employees.

Purpose of the role:   To design, build and operationalise Copilot‑based and LLM‑powered solutions, focusing on secure engineering, enterprise integration and reusable accelerators that reduce vendor dependency and increase internal delivery velocity.

Key Accountabilities

Role Specific Accountabilities

• Design, develop and maintain Copilot solutions, intelligent agents, plugins, connectors and LLM workflows (e.g., Copilot Studio).
• Build scalable components (prompt orchestration, retrieval layers, automation flows, model interfaces, validation pipelines).
• Integrate with enterprise systems/APIs/data platforms, ensuring security, resilience and architecture alignment.
• Conduct rapid prototyping to validate feasibility, model behaviour, UX and performance.
• Implement secure‑by‑design and responsible AI practices (guardrails, controls, monitoring, auditability).
• Develop/optimise RAG components, embeddings, vector queries and metadata strategies for accuracy/reliability.
• Implement observability: logging, telemetry and LLM monitoring for quality and incident triage.
• Create reusable assets (prompt libraries, agent templates, connectors, test harnesses) and documentation.
• Translate design artefacts into build‑ready specifications and aligned solution designs.
• Co‑define test strategies and model performance thresholds with the AI Test Lead.
• Contribute to cross‑functional design/architecture reviews and standards evolution.
• Mentor colleagues and enable pro‑/low‑/no‑code teams to adopt AI safely.
• Ensure responsible AI principles (e.g., transparency, explainability, ISO42001) are incorporated into all development.
• Provide insight to support business cases, investment decisions, risk assessments, and prioritisation discussions at AI governance forums.
• Collaborate with teams to ensure all AI development work is implementable, sustainable and aligned to enterprise architecture.
• Maintain a library of development artefacts, patterns and re‑usable assets to support repeatability and uplift maturity across the AI Foundry.
• Managing escalations supporting the wider Data & AI Leadership team.

Shared Accountabilities

• Translate Divisional priorities into plans and deliverables to deliver overall Group strategic priorities
• Build the capability & capacity of functional resources to drive sustained commercial success
• Interpret & communicate the priorities for the Function, motivating and developing a high performing team
• Own functional priorities, applying specialist expertise to put the customer at the heart of everything and drive a profitable business
• Initiate and develop critical external and internal relationships which create value, collaborating to deliver commercial and customer priorities
• Uphold corporate legal & regulatory responsibilities
• Implement and manage transformation activity & harness innovation to create a high performing & sustainable business

Functional/Technical (Role Specific)

Essential

• Higher education qualification (or equivalent experience) in Ethics, Law, Risk Management, Social Sciences, Data/Computer Science or relevant field
• Proven hands‑on experience building solutions using LLMs, AI APIs, Copilot Studio or agent frameworks.
• Strong understanding of vector databases, embeddings, RAG architectures and retrieval optimisation.
• Experience implementing secure‑by‑design practices including authentication, authorisation, data protection and auditability.
• Experience working within Microsoft Foundry‑style model and agent engineering, including LLM orchestration, RAG component optimisation, agent lifecycle management, versioning, monitoring, drift detection, and building reusable model/agent components governed under enterprise controls.
• Experience working with Microsoft Azure AI and cloud-native engineering, including integration with Azure AI services, secure deployment patterns, observability, telemetry, vector search and embeddings, and alignment with enterprise-grade cloud architectures used across the AI Foundry.
• Familiarity with DevOps, CI/CD, IaC, observability, monitoring and modern engineering pipelines.
• Ability to translate complex requirements or user needs into scalable, maintainable technical solutions.
• Ability to debug unexpected AI or model behaviour, including hallucinations, variability and reliability issues.
• Strong documentation skills and ability to produce reusable code assets, templates and guidance.
• Collaborative working style with analysts, testers and architects throughout delivery.
• Comfortable learning and adapting to emerging AI technologies and engineering patterns.
• Excellent stakeholder management and communication skills, including senior‑level engagement.
• Commercial awareness and a value‑driven mindset.
• Familiarity with AI ethics, fairness, transparency and accountability principles
• Use of professional networks and external influencers with clear evidence of learning and development to build and maintain skills and expertise

Sector (desirable)

• Understanding of financial services industry, markets and competitors
• Understanding of how financial services organisations operate and the associated regulatory environment, or other regulated industries
• Awareness of the Mutual Sector and the needs and interests of Members