Architecture & solution leadership

• Own architecture, design, and implementation of enterprise-grade GenAI and Agentic AI solutions from concept to production.
• Define scalable reference architectures and design patterns for AI platforms, copilots, and intelligent agents.
• Establish architectural standards, reusable components, and best practices across delivery programs.
• Design secure, resilient, highly available AI systems at enterprise scale, across structured and unstructured data.

Generative & Agentic AI delivery

• Design and deliver LLM-powered applications: conversational AI, enterprise copilots, knowledge management, and workflow automation.
• Architect advanced retrieval using RAG, Agentic RAG, Graph RAG, knowledge-graph, and hybrid approaches.
• Design multi-agent systems with modern orchestration and reasoning architectures, including human-in-the-loop and autonomous frameworks.
• Define memory, context, planning, tool-use, and reasoning strategies for agentic systems.

Hands-on engineering

• Stay technical. Contribute to architecture, critical-path code, design reviews, and the hardest technical problems.
• Design APIs, microservices, and cloud-native AI services that underpin enterprise AI ecosystems.
• Guide teams on software architecture, performance, scalability, security, and maintainability.

AI governance & LLMOps

• Architect governance frameworks for auditability, observability, explainability, and compliance.
• Design guardrails for hallucination, prompt injection, toxicity, and model safety.
• Establish LLMOps: evaluation pipelines, automated testing, CI/CD, monitoring, and production governance.
• Define evaluation frameworks spanning quality, safety, reliability, latency, and business outcomes.

Qualifications and experience we consider to be essential for the role:

• 10–15 years across software engineering, AI/ML, data science, or enterprise architecture, with a clear trajectory into senior technical leadership.
• Proven track record architecting and deploying production-scale AI, from strategy through implementation.
• Experience in a consulting, services, or client-facing delivery environment, including supporting pre-sales or solution shaping.
• Experience leading globally distributed, multi-disciplinary teams.
• Bachelor’s in Computer Science, AI, Engineering, Data Science, or a related field. Master’s preferred.

Skills and Personal attributes we would like to have:

Core Knowledge Expected

• Programming & engineering: expert Python; REST APIs and microservices; FastAPI; distributed systems; cloud-native architecture.
• LLM application delivery: prompt engineering, tool and function calling, RAG, and at least one production Agentic AI system.
• Cloud AI platform: deep experience with one of Azure, OpenAI, AWS Bedrock, Claude; Kubernetes and cloud-native deployment.
• LLMOps & evaluation: CI/CD for AI, automated evals, experiment tracking, observability, model lifecycle management.
• Responsible AI: governance frameworks, guardrails, model safety, compliance, and auditability.

Preferred but not required

• Orchestration frameworks: LangChain / LangGraph, LlamaIndex, CrewAI, AutoGen, DSPy, Semantic Kernel, Strands.
• Advanced retrieval: Graph RAG, knowledge graphs, context graphs, hybrid search, vector databases.
• Agentic patterns: multi-agent architectures, planning and reasoning, MCP (Model Context Protocol).
• Model customization: fine-tuning, distillation, and model evaluation at scale.
• Frontier model families: OpenAI, Claude, Gemini, Llama, Mistral.

What success looks like in this role.

In the first 12 months

• Multiple enterprise GenAI and Agentic solutions delivered into production to deliver value / outcomes.
• Reference architectures and reusable accelerators adopted across programs, measurably reducing delivery time or cost.
• AI governance, evaluation, and observability standards operational on live engagements.

Ongoing

• Recognised as the primary technical authority for complex client AI initiatives and executive relationships.
• Technical leadership converts into won and expanded engagements and a growing qualified pipeline.
• A stronger, higher-performing AI engineering team, with you still close to the technology.

As part of a leading global Data and AI company, you can look forward to:

• A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension.
• EXL provides everyday financial well-being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers. We also offer a Cycle Scheme where you can save money on bikes and cycling accessories.
• At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies.
• As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status.
• EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP).
• At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration.

To be considered for this role, you must already be eligible to work in the United Kingdom.