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About the Role

Enterprises are past GenAI experimentation and now demand production systems with measurable ROI, governance, and scale. This role is the senior technical authority who converts ambitious client mandates into secure, production-grade Generative and Agentic AI systems, and turns each engagement into reusable IP that compounds EXL’s delivery leverage and pipeline.

Responsibilities

Partner with sales and practice leaders to shape pursuits, solution complex deals, and influence SOWs, estimates, and delivery approach.
Serve as the senior technical voice in client pursuits and executive conversations, converting technical credibility into won and expanded engagements.
Build reusable accelerators, reference architectures, and IP that lower delivery cost and differentiate EXL in the market.
Identify expansion opportunities within accounts and translate delivered outcomes into follow-on pipeline.
Lead and grow global, multi-disciplinary AI teams, and raise the technical bar across the practice.
Partner with business and technology leaders to define AI roadmaps and implementation strategy.
Mentor architects and engineers, and build a bench of senior technical talent.
Translate complex architectures for executive and non-technical audiences.
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.
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.
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.
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.

Requirements

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.
Must already be eligible to work in the United Kingdom.

Skills

Expert Python
REST APIs and microservices
FastAPI
Distributed systems
Cloud-native architecture
Prompt engineering
Tool and function calling
RAG
Production Agentic AI system
Azure
OpenAI
AWS Bedrock
Claude
Kubernetes
Cloud-native deployment
CI/CD for AI
Automated evals
Experiment tracking
Observability
Model lifecycle management
Governance frameworks
Guardrails
Model safety
Compliance
Auditability
LangChain / LangGraph
LlamaIndex
CrewAI
AutoGen
DSPy
Semantic Kernel
Strands
Graph RAG
Knowledge graphs
Context graphs
Hybrid search
Vector databases
Multi-agent architectures
Planning and reasoning
MCP (Model Context Protocol)
Fine-tuning
Distillation
Model evaluation at scale
Frontier model families: OpenAI, Claude, Gemini, Llama, Mistral

Location

London, United Kingdom

Work Type

Permanent
Flexible hybrid working

Experience Level

Senior technical leadership
Vice President

Education Level

Bachelor’s in Computer Science, AI, Engineering, Data Science, or a related field
Master’s preferred

Salary/Compensations

Competitive salary with a generous bonus

Benefits

Private healthcare
Critical illness life assurance at 4 x your annual salary
Income protection insurance
Rewarding pension
Everyday financial well-being solutions, such as cash back cards
Cycle Scheme
Wide range of professional and personal development opportunities
Support for a range of learning initiatives
Employee Stock Purchase Plan (ESPP)

About the Company

EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed.
EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others.
EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect.
Headquartered in New York with more than 60,000 employees spanning six continents.

Equal Opportunity

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.