Agentic AI Engineer

Job Title : Agentic AI Engineer

Experience : 4 to 6 years

Notice period : Immediate Joiner to 15 days

Location : Bengaluru

Job Description :

Role Overview

We are looking for an AI Engineer specializing in Agentic AI systems and cloud-native deployment. This role focuses on building intelligent, autonomous systems using LLMs, RAG architectures, and emerging protocols like MCP, with an emphasis on scalable, production-ready implementations.

Key Responsibilities

· Design and build Agentic AI systems capable of planning, reasoning, and tool usage

· Develop and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases

· Implement and integrate Model Context Protocol (MCP) or similar frameworks for tool orchestration

· Build multi-agent workflows and autonomous decision-making systems

· Deploy AI applications on cloud platforms (AWS, Azure, GCP) with scalability and reliability

· Develop APIs and services to integrate LLM-powered features into products

· Work with vector databases and retrieval systems for efficient knowledge access

· Optimize latency, cost, and performance of LLM-based applications

· Implement observability, monitoring, and evaluation frameworks for AI systems

· Collaborate with product and engineering teams to deliver production-grade AI solutions

Required Skills & Qualifications

· 4–6 years of experience in software engineering or AI engineering roles

· Strong proficiency in Python and modern backend frameworks (FastAPI, Flask, etc.)

· Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or similar

· Strong understanding of RAG architectures, embeddings, chunking, and retrieval strategies

· Experience with vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.)

· Experience building agentic workflows (tool use, memory, planning, orchestration)

· Familiarity with MCP (Model Context Protocol) or similar tool-interaction paradigms

· Experience deploying AI applications on cloud platforms (AWS/Azure/GCP)

· Strong knowledge of Docker, Kubernetes, and microservices architecture

· Experience designing and consuming REST APIs / async systems

Preferred Qualifications

· Experience with multi-agent systems and orchestration frameworks

· Familiarity with prompt engineering, evaluation, and guardrails

· Knowledge of LLM observability tools (LangSmith, Weights & Biases, etc.)

· Experience with streaming architectures and real-time AI systems

· Exposure to security and governance in AI systems

· Understanding of cost optimization strategies for LLM usage

Soft Skills

· Strong problem-solving and system design skills

· Ability to work in fast-evolving AI landscapes

· Good communication and cross-functional collaboration