GenAI Engineer - LLM/RAG

GenAI Engineer

Location: Hyderabad, Chennai, Bangalore, Pune

Experience: 5 to 11 Years

About the Role:

We are looking for experienced GenAI Engineers with strong hands-on expertise in Machine Learning, Generative AI, LLM integration, RAG architectures, AI agents, and scalable AI deployment. The ideal candidate should have practical experience in developing, integrating, deploying, and monitoring production-grade AI and GenAI solutions.

Key Responsibilities:

Generative AI and Machine Learning:

- Design, develop, and deploy Machine Learning and Generative AI solutions.

- Build and integrate LLM-based applications for enterprise use cases.

- Perform model experimentation, fine-tuning, evaluation, deployment, and monitoring.

- Develop scalable and production-ready AI solutions.

- Work closely with Data Science, Data Engineering, and Product teams.

LLM and RAG:

- Develop applications using LLMs such as OpenAI, BERT, LLaMA, and Gemini.

- Build and optimize Retrieval-Augmented Generation pipelines.

- Integrate and work with Vector Databases.

- Develop knowledge retrieval and context management solutions.

- Implement prompt engineering and optimization techniques.

- Evaluate LLM performance, accuracy, latency, and cost.

AI Agent Development:

- Design and develop AI agents for automation and intelligent workflows.

- Implement agent orchestration and tool integration.

- Develop scalable agentic AI solutions for enterprise use cases.

Model Deployment and MLOps:

- Deploy and monitor machine learning and GenAI models in production environments.

- Use MLflow for experiment tracking and model lifecycle management.

- Work with Docker and Kubernetes for containerized AI deployments.

- Implement monitoring, logging, and observability for AI applications.

- Follow CI/CD and MLOps best practices.

Security and Compliance:

- Implement security best practices for LLM and GenAI applications.

- Ensure appropriate handling of enterprise data and sensitive information.

- Support AI governance, compliance, and responsible AI practices.

Required Skills:

- 5 to 11 years of experience in Machine Learning, AI, Data Science, or related fields.

- Strong hands-on experience in Generative AI and LLM-based applications.

- Experience with LLMs such as OpenAI, BERT, LLaMA, and Gemini.

- Strong experience in RAG pipeline development.

- Hands-on experience with Vector Databases.

- Experience in AI Agent design and development.

- Strong understanding of Prompt Engineering.

- Experience with model design, fine-tuning, experimentation, deployment, and monitoring.

- Strong programming skills in Python.

- Experience with TensorFlow and/or PyTorch.

- Experience with MLflow.

- Experience with Docker and Kubernetes.

- Knowledge of scalable AI deployment and production ML systems.

- Understanding of AI security and compliance requirements.