Overview
In this role you lead the Generative AI Technologies team to shape Infosys’ AI strategy and deliver enterprise-scale Gen AI solutions. You will select models, design architectures, and collaborate with cross-functional teams to meet customer goals. You’ll balance innovation with practical deployment, focusing on scalable, secure, and cost-efficient AI ecosystems. This position offers the opportunity to influence AI-first strategy and advance cutting-edge capabilities across industries.
Pay / Benefits
- Competitive compensation including bonus
- London, UK location
Responsibilities
- Lead Generative and Agentic AI strategy and roadmapping aligned with business goals
- Evaluate and select models, frameworks, RAG strategies, and MCP-based integration standards
- Design end-to-end architectures for data preprocessing, training, deployment, and monitoring
- Define reusable agentic architecture patterns, memory/state management, and guardrails for production
- Collaborate with data scientists and engineers to implement production-grade AI solutions
- Optimize performance, latency, and cost of AI systems, with ongoing experimentation
- Assess outcomes against success criteria and iterate on models and strategies
- Engage with customer teams to define requirements, boundaries, and SLAs; mentor junior staff
- Stay current with Gen AI landscape and incorporate trends into solutions and platform architecture
Key requirements
- Deep Generative AI expertise across LLMs, diffusion, multimodal models; hands-on with API-based and open-source LLMs
- Expertise in agentic AI, multi-agent design, and tool-driven workflows; familiarity with LangGraph, CrewAI, MAF, ADK, OpenAI Agents SDK
- Strong MCP knowledge for standardized LLM/tool integration and enterprise interoperability
- Experience extending agent capabilities via modular skills and reusable components
- RAG and knowledge-architecture experience; embeddings, vector stores, hybrid search, and evaluation
- LLMOps, observability, governance, safety, bias/fairness, and regulatory considerations
- Proficiency in Python and ML frameworks; experience with LangChain, LlamaIndex, Semantic Kernel; cloud AI platforms
- excellent communication and collaboration
- ability to convey complex concepts to non-technical stakeholders
- customer orientation and proactive leadership
- Python
- TensorFlow
- PyTorch
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