Lead / Senior GenAI Engineer – AI & Data Team Experience

5 – 15 Years

Employment Type

Full-Time

Location

India (Remote/Hybrid as per business requirements)

About the Role

We are seeking highly skilled and innovative Generative AI professionals to join our AI & Data team. This role offers an opportunity to design, develop, and deploy enterprise-scale AI solutions that drive meaningful business outcomes for global organizations.

The ideal candidate will have extensive experience in building production-grade Generative AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Agentic AI frameworks, and modern AI/ML technologies. You will work closely with cross-functional teams to solve complex business challenges and deliver scalable, high-impact AI solutions.

Key Responsibilities Generative AI Solution Development

Design, develop, and deploy enterprise-grade Generative AI applications.

Build intelligent solutions using LLMs, RAG architectures, AI Agents, and multi-agent systems.

Develop and optimize prompt engineering strategies for accuracy, performance, and reliability.

Implement agentic workflows using modern AI frameworks and orchestration tools.

Evaluate, fine-tune, and optimize foundation models for business-specific use cases.

AI Engineering & Architecture

Design scalable AI architectures capable of supporting production workloads.

Build robust APIs, microservices, and AI pipelines for enterprise deployment.

Develop monitoring, evaluation, and governance mechanisms for AI applications.

Ensure security, scalability, reliability, and responsible AI practices across deployments.

Data Science & Machine Learning

Develop advanced machine learning and deep learning solutions where applicable.

Build and optimize data pipelines supporting AI and analytics initiatives.

Apply statistical and machine learning techniques to solve complex business challenges.

Collaborate with data engineering teams to ensure high-quality data availability.

Cloud & MLOps

Deploy and manage AI solutions on Azure, AWS, or Google Cloud Platform.

Implement CI/CD pipelines and MLOps best practices for AI model lifecycle management.

Leverage containerization technologies such as Docker and orchestration platforms like Kubernetes.

Optimize infrastructure costs and performance for AI workloads.

Stakeholder Collaboration

Partner with business stakeholders to understand requirements and translate them into AI solutions.

Present technical concepts and solution recommendations to leadership teams.

Mentor junior team members and contribute to AI best practices and knowledge sharing.

Required Qualifications Experience

5–15 years of experience in AI/ML, Data Science, Software Engineering, or related domains.

Demonstrated experience building and deploying production-grade Generative AI solutions.

Proven track record of delivering measurable business impact through AI initiatives.

Technical Skills Generative AI & LLMs

Strong hands-on experience with:

Large Language Models (OpenAI, Claude, Llama, Gemini, Mistral, etc.)

Retrieval-Augmented Generation (RAG)

AI Agents and Multi-Agent Systems

Prompt Engineering

Agentic AI Frameworks

Model Evaluation and Optimization

AI Frameworks & Libraries

Expertise in:

LangChain

LangGraph

LlamaIndex

CrewAI

AutoGen

Semantic Kernel

Hugging Face Ecosystem

Programming

Advanced proficiency in Python.

Strong software engineering fundamentals.

Experience with REST APIs, FastAPI, Flask, or similar frameworks.

Cloud Platforms

Hands-on experience with at least one of:

Microsoft Azure

Amazon Web Services (AWS)

Google Cloud Platform (GCP)

Databases & Vector Stores

Experience with:

Pinecone

Weaviate

ChromaDB

FAISS

Elasticsearch/OpenSearch

SQL and NoSQL databases

DevOps & MLOps

Docker

Kubernetes

Git

CI/CD Pipelines

Model Monitoring & Governance

Preferred Qualifications

Experience in Life Sciences, Healthcare, Pharmaceutical, or Commercial Analytics domains.

Exposure to enterprise AI governance frameworks.

Experience with Responsible AI, model explainability, and compliance requirements.

Knowledge of NLP, Knowledge Graphs, and advanced search systems.

Experience leading AI teams or mentoring engineers.

What Success Looks Like

Delivering scalable AI applications used by business teams and clients.

Driving measurable productivity, automation, and decision-making improvements.

Building reusable AI accelerators and frameworks.

Establishing best practices for enterprise AI development and deployment.

Why Join Us

Work on cutting-edge Generative AI and Agentic AI initiatives.

Solve complex business challenges using state-of-the-art AI technologies.

Collaborate with highly experienced AI, Data Science, and Engineering professionals.

Build solutions that create significant business value for global organizations.

Opportunity to influence the future of enterprise AI adoption at scale.

Notice Period

Immediate joiners or candidates with a short notice period will be preferred.

You can add the following hashtags at the end of the JD or LinkedIn post:

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