Lead Data & AI Scientist

Lloyds Technology Centre

Hyderabad, INhybridPosted Jul 16, 2026
Posting intelligenceActively listedReposted 3×, possible evergreen/ghost posting

Skills

langchainnaturallanguageprocessingllmml

About the role

End Date

Wednesday 22 July 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

Leads the desigining of patterns, tooling, and templates to rapidly and efficiently deploy models into production. Scales AI/ML solutions on strategic infrastructure and integrating them into existing systems. Acts as a point of technical expertise and thought leadership, and provides line management and/or coaching to grow team capability.

Job Description

Exp : 15+ years

Location : Hyderabad

We are looking for a hands-on Lead Data & AI Scientist to drive the design, development, and scaling of AI-powered solutions across the enterprise. This role will shape our AI/ML strategy, mentor high-performing teams, and deliver impactful outcomes using cutting-edge technologies like GenAI, autonomous agents, NLP, and advanced ML .

What You’ll Do

Lead end-to-end development of scalable AI/ML solutions for complex business problems

Design and implement GenAI systems (RAG pipelines, autonomous agents)

Evaluate and optimise LLMs (GPT, LLaMA, Claude, Mistral) for business use cases

Collaborate with cross-functional teams to integrate AI into products/platforms

Drive experimentation, rapid prototyping, and continuous innovation

Mentor data scientists and engineers, fostering a culture of excellence

Establish best practices for MLOps, governance, and model lifecycle management

What We’re Looking For

Strong foundation in Statistics, Machine Learning, and Deep Learning

Hands-on experience with GenAI frameworks (LangChain, LangGraph, etc.)

Expertise in NLP (semantic search, NER, text generation)

Experience building and deploying LLM-based solutions and fine-tuning models

Ability to design autonomous AI agents (planning, reasoning, action)

Proven experience working with large datasets and scalable AI systems

Exposure to MLOps/AIOps for production-grade deployments

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