Senior Lead Analyst - Data Science_ AI/ML & Gen AI

ITL UK
London
3 weeks ago
Create job alert

Job Description

Infosys is seeking a Senior AI/ML & Generative AI Engineer with deep expertise in designing, developing, and deploying advanced AI solutions. This includes core Python development using OOPs concepts, Large Language Models (LLMs), and Agentic AI architectures. The ideal candidate will collaborate with clients to understand complex business challenges, architect scalable AI solutions, and deploy them using modern cloud platforms such as AWS, Azure ML and GCP AI Services.This role offers the opportunity to work on cutting-edge technologies in Generative AI, LLM fine-tuning, agentic orchestration, and vector databases, while shaping impactful consulting solutions across industries like Banking, Finance, and Capital Markets.________________________________________Your RoleAs a Senior Lead Analyst, you will:•Anchor the engagement effort from business process consulting and problem definition to solution design, development, and deployment.•Lead the discovery and definition of AI/ML solutions and guide teams on project processes and deliverables.•Act as a thought leader in your domain, advising on architecture and design reviews.•Drive business pursuit initiatives, client training, and in-house capability building.•Shape value-adding consulting solutions that help clients meet evolving business needs.________________________________________Responsibilities•Develop the core Python Programs using oops Concepts.•Design and develop scalable AI/ML solutions using Python and cloud platforms.•Lead the implementation of Generative AI models, LLMs, and agentic frameworks.•Collaborate with stakeholders to define problem statements and solution approaches.•Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines.•Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines.•Ensure high-quality delivery and adherence to best practices in AI/ML engineering.________________________________________Required•Minimum 7 years of experience in Information Technology.•Minimum 5 years in Python programming, including OOPs, data structures, Stacks, Queues, Scripting, Linkedlists, Arrays, and API development.•Minimum 5 years in Big Data technologies (e.g., , Hadoop).•Minimum 4 years in cloud platforms (AWS, Azure, GCP) and their AI/ML services.•Minimum 5 years in ML model development, data engineering, and software engineering.•Minimum 3 years in MLOps and AI/ML deployment.•Minimum **2 years in Generative AI, LLMs, and agentic frameworks.________________________________________Preferred•Experience with API Gateway development and deployment on Azure/GCP.•Hands-on experience with vector databases and RAG pipelines.•Familiarity with CI/CD, DevOps, and automation tools in AI/ML contexts.•Strong problem-solving and stakeholder management skills.•Domain expertise in Banking, Finance, or Capital Markets.________________________________________Personal Attributes•High analytical skills•Strong initiative and flexibility•High customer orientation•Strong quality awareness•Excellent verbal and written communication skills________________________________________Why InfosysInfosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey.We do this by enabling the enterprise with an AI-powered core and agile digital at scale to deliver unprecedented performance and customer delight. Our always-on learning agenda drives continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.Infosys is proud to be an equal opportunity employer. All aspects of employment are based on merit, competence, and performance. We are committed to embracing diversity and creating an inclusive environment for all employees.

Related Jobs

View all jobs

Senior Lead Analyst - Data Science - Machine Learning & Gen AI - UK

Senior Lead Analyst - Data Science_ AI/ML & Gen AI - UK

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Senior Data Scientist

Data Scientist (GIS) – Remote

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.