Senior GenAI Engineer

Office in India: Chennai, India: Coimbatore

AI Engineering

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We are seeking a highly skilled Senior GenAI Engineer to lead the design, development, and deployment of cutting-edge Generative AI, LLM-based, and agentic AI solutions that power transformative business applications.

Responsibilities

Lead the end-to-end development and fine-tuning of Generative AI, LLMs, and agentic AI models for production use cases
Architect RAG pipelines, manage embeddings, and optimize performance of deployed models
Design and implement AI agents and multi-agent systems to automate complex workflows
Integrate AI models, agents, and multi-agent architectures seamlessly with APIs, backend systems, and data pipelines
Collaborate with data engineering, product management, and business teams to deliver impactful AI-powered solutions
Establish and enforce MLOps best practices for scalable, reproducible machine learning operations
Promote AI governance, adhering to security protocols and ethical standards in solution development
Ensure effective utilization of vector databases for model training, inference, and production workflows
Leverage cloud AI platforms to build scalable and secure AI/ML solutions that meet business objectives
Provide technical leadership and mentorship to the team to drive innovation and maximize technical competency

Requirements

5+ years of professional experience in AI/ML, with at least 2 years dedicated to Generative AI, LLM development, and agentic AI solutions
Proficiency in Python and deep learning frameworks like PyTorch and TensorFlow
Expertise in GenAI tools and libraries, including Hugging Face Transformers, LangChain, and RAG
Background in agentic AI frameworks such as LangChain Agents, OpenAI Function Calling, AutoGen, CrewAI, and MetaGPT
Knowledge of vector databases like FAISS, Qdrant, Chroma, and Pinecone
Competency in cloud AI/ML platforms such as AWS SageMaker, AWS Bedrock, Azure OpenAI Service, Azure Machine Learning, and Google Vertex AI
Skills in containerization and integration with Docker, Kubernetes, RESTful APIs, and microservices
Understanding of MLOps best practices, AI governance, and ethical AI principles
Strong communication and leadership skills with a demonstrated ability to deliver enterprise-grade AI solutions