We are seeking a highly skilled AI Developer (Agentic AI) at SDE2 level to join our cutting-edge team in Bangalore.

The ideal candidate will be experienced in developing and deploying intelligent AI systems leveraging LLMs, LangChain, and advanced agentic frameworks.

This role demands hands-on expertise in Python, LLM integrations, RAG pipelines, and scalable MLOps practices on cloud environments.

Key Responsibilities :

- Design, develop, and deploy Agentic AI systems using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.

- Integrate Large Language Models (LLMs) such as OpenAI, Anthropic, or similar into production-grade applications.

- Build RAG (Retrieval-Augmented Generation) pipelines utilizing Vector Databases like Pinecone, Milvus, or FAISS.

- Develop and optimize prompt orchestration, reasoning chains, and multi-agent collaboration workflows.

- Implement MLOps pipelines for continuous training, model deployment, and performance monitoring.

- Collaborate with data engineers, ML researchers, and backend teams to integrate AI systems into enterprise-grade products.

- Ensure system scalability, latency optimization, and secure API interactions across cloud platforms (AWS/GCP/Azure).

- Evaluate emerging AI frameworks, libraries, and methodologies to enhance agentic automation and self-improving AI architectures.

Required Technical Skills :

- Programming : Advanced Python (async programming, API integrations, and modular architectures).

- AI Frameworks : LangChain, LangGraph, AutoGen, CrewAI (hands-on experience mandatory).

- LLM Ecosystem : Experience integrating models from OpenAI, Anthropic, Cohere, or similar.

- Vector Databases : Pinecone, Milvus, FAISS, or Weaviate for semantic search and memory management.

- RAG Pipelines : Data retrieval, document indexing, embedding generation, and contextual response generation.

- Cloud Platforms : AWS / GCP / Azure (AI & ML services, container orchestration).

- MLOps : CI/CD for ML, Docker, Kubernetes, Model Registry, and deployment automation.

- Version Control : Git, GitHub Actions, or equivalent.

Preferred Skills :

- Familiarity with multi-agent systems, autonomous decision-making frameworks, and reasoning graph design.

- Experience in API development (FastAPI / Flask) and integrating AI capabilities into web or enterprise solutions.

- Exposure to observability tools (Prometheus, Grafana) and performance monitoring for LLM-based workloads.

- Understanding of data privacy, model fine-tuning, and prompt engineering best practices.

Educational Qualification :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related field