Job Description

Role: Senior Technology Architect

Specialization: GenAI, LLM, RAG, Agentic AI, AI Workflows

Location: London, United Kingdom

Unit: ENG

Remuneration: Competitive (inclusive of performance bonuses)

Core Objective

The AI Architect oversees the creation and execution of AI-powered product features across diverse sectors, including Aerospace, Manufacturing, Retail, and Finance, utilizing both Conventional and Generative AI alongside Machine Learning.

This position entails establishing architectural frameworks, mentoring development squads, and fostering advancement within AI/ML, Large Language Models, Retrieval-Augmented Generation, and Agentic AI scenarios. The successful applicant merges profound technical expertise with a product-oriented focus, cooperative spirit, and leadership. Qualifications include technical advisory skills, solution design proficiency, and industry-specific knowledge relevant to GenAI applications. The candidate must facilitate value stream sessions to identify AI integration opportunities and formulate comprehensive architectural blueprints. Superior verbal and written communication is essential.

Primary Accountabilities:

Construct and deploy elastic GenAI frameworks across data, model, and software tiers.
Standardize reference architectures, repeatable templates, and optimal protocols for embedding AI into products.
Engineer and manage the lifecycle of LLM, RAG, Copilot, and Agentic AI systems.
Maintain proficiency in ML and successfully merge AI/ML methodologies.
Implement MLOps and GenAIOps structures for model maintenance, oversight, and compliance.
Partner with product, data, and software engineering departments to convert commercial requirements into AI-driven capabilities.
Direct Proof of Concept (PoC) projects and R&D efforts to assess new platforms and tech.
Instruct personnel on AI development, prompt engineering, and high-volume deployment strategies.
Assist in pre-sales activities and client consultations to outline solution strategies and architectural paths.
Understand the Product Development Value Chain within a specific industry.

Technical Proficiencies & Background:

Robust grounding in Natural Language Processing and LLM-centric systems.
Acquaintance with machine learning and deep learning (Advanced expertise is highly valued).
Practical command of Python, TensorFlow, PyTorch, LangChain, LangGraph/CrewAI/AutoGen, Hugging Face, and MLflow.
Familiarity with cloud-based AI environments – AWS (SageMaker, Bedrock), Azure (AI Studio, OpenAI), or GCP (Vertex AI), plus GraphRAG.
Experience involving Foundation models, Codex plugins, and modern coding utilities (Cursor, Devin).
Understanding of vector database technologies (such as Pinecone, Weaviate, FAISS, MILVUS) and RAG architecture.
Competency with container tools (Docker, Kubernetes) and MLOps procedures.
Knowledge of prompt optimization, model fine-tuning, assessment, and ethical AI frameworks.
Grasp of data engineering, model transparency, and AI regulatory oversight.

Interpersonal Skills:

Potent investigative, troubleshooting, and articulation talents.
Team-focused attitude with the capacity to interface with product, engineering, and data units.
Visionary leadership in championing AI integration, novelty, and industry standards.
Background in supporting AI Centers of Excellence (CoE) and client-facing projects.

Job Data Table

Category	Details
Company Name	Infosys (ITL UK)
Location	London, United Kingdom
Locality	London
Country	United Kingdom
City	London
Region	London
Job Type	Full-time
Salaries	Competitive (including bonus)
Experience Level	Senior
Travel	Not Specified
Language	English
Benefits	Competitive Compensation, Bonus, Inclusive Environment

Skills & Competency Table

Skill	Competency Level
GenAI, LLM, RAG Architecture	Expert
Agentic AI & Workflows	Expert
Python, TensorFlow, PyTorch	Advanced
MLOps & GenAIOps	Advanced
Cloud AI (AWS/Azure/GCP)	Advanced
Technical Consulting	Advanced
Solutioning & Architecture	Expert
Prompt Engineering & Fine-tuning	Advanced

Salaries Pay Calculator Table

Component	Amount	Notes
Annual Salary	Competitive	Based on market rates for London
Bonus	Included	Performance-based incentives
Total Compensation	Competitive + Bonus	Commensurate with senior expertise

Job Summary

This Senior AI Architect role focuses on leading the design and deployment of scalable Generative AI and Machine Learning solutions. Based in London, you will drive innovation across multiple industries, define reference architectures for LLM and Agentic AI, and bridge the gap between complex business needs and advanced technical implementation.

FAQs

What are the primary technologies used in this role?

The role focuses on GenAI, LLM, RAG, Agentic AI, Python, and cloud ecosystems like AWS, Azure, or GCP.

Is previous leadership experience required?

Yes, the role requires leading PoCs, mentoring teams, and providing thought leadership for AI adoption.

Which industries will I work with?

You will design solutions for various domains including Aerospace, Manufacturing, Retail, and Finance.

What is the focus of the “Agentic AI” responsibility?

It involves designing and operationalizing automated AI workflows and agent-based system architectures.

Does this role involve client interaction?

Yes, you will support pre-sales, conduct value stream workshops, and engage in customer architectural discussions.

Expert Analysis

This position is a high-level strategic role that demands a rare blend of hands-on engineering and broad architectural vision. As AI shifts from experimental to operational, this architect will be pivotal in establishing governance (MLOps) and scalable frameworks, making it ideal for a leader in the GenAI space.

Location & Logistics Guide

The role is based in London, a global hub for technology and finance. London offers a robust infrastructure for tech professionals and a high density of AI research centers.

City Wikipedia URL: https://en.wikipedia.org/wiki/London

Career Path

A Senior Technology Architect at Infosys can transition into a Principal Architect or Chief Technology Officer (CTO) within specialized AI units. Success in this role opens opportunities to lead global Centers of Excellence or move into strategic product management, overseeing the entire AI product lifecycle for enterprise clients.

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