Senior AI/ML Engineer - RAG/Agentic AI

Job Title : Senior AI/ML Engineer - Agentic AI / RAG / LLM

Experience : 5 - 12 Years

Location : Bangalore / Noida

Employment Type : Full Time

Industry : Product-Based Company

Job Description :

We are looking for highly skilled and passionate AI/ML Engineers with strong expertise in Generative AI, Agentic AI frameworks, RAG architectures, and Large Language Models (LLMs) to join our growing product engineering team.

The ideal candidate will have hands-on experience building scalable AI-powered applications, designing intelligent autonomous workflows, and deploying production-grade GenAI solutions using modern AI/ML technologies and cloud ecosystems.

This is an exciting opportunity to work on cutting-edge AI products and contribute to next-generation intelligent platforms.

Key Responsibilities :

- Design, develop, and deploy scalable AI/ML and Generative AI solutions.

- Build intelligent applications using :

1. Agentic AI frameworks

2. Retrieval-Augmented Generation (RAG)

3. Large Language Models (LLMs)

- Develop autonomous AI workflows with :

1. Tool calling

2. Multi-agent orchestration

3. Memory management

4. Context engineering

- Implement and optimize :

1. Prompt engineering

2. Fine-tuning

3. Embedding pipelines

4. Vector database integrations

- Build and maintain end-to-end AI/ML pipelines for training, inference, evaluation, and monitoring.

- Work with structured and unstructured data for AI model development.

- Collaborate with product, engineering, and business teams to translate AI use cases into

scalable solutions.

- Optimize AI model performance, scalability, reliability, and observability.

- Ensure best engineering practices including CI/CD, testing, and deployment automation.

Mandatory Skills :

- 5 - 12 years of experience in AI/ML, Data Science, or Software Engineering.

- Strong hands-on expertise in :

1. Python

2. Machine Learning

3. Deep Learning

4. NLP

- Strong experience with :

1. Generative AI

2. Large Language Models (LLMs)

3. Agentic AI frameworks

4. Retrieval-Augmented Generation (RAG)

- Hands-on experience with :

1. LangChain

2. LangGraph

3. LlamaIndex

4. OpenAI APIs

5. Hugging Face

- Experience with :

1. Prompt Engineering

2. Fine-tuning

3. Embeddings

4. Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)

- Good understanding of :

1. AI/ML lifecycle

2. Model evaluation

3. MLOps concepts

4. AI deployment architectures

- Experience with cloud platforms such as AWS, Azure, or GCP.