Senior Agentic AI Developer

Cai Info India; Bengaluru; Hybrid; INR 3,500,000 - 6,000,000; Full time

Job summary

Cai Info India is seeking a Senior Agentic AI Developer to design and deploy multi-agent systems and autonomous workflows in a hybrid Bengaluru setting. You will shape agent-to-agent communication, MCP, and RAG-based architectures while leveraging OpenAPI and cloud platforms.

The role emphasizes building scalable AI solutions, memory/planning capabilities, and cutting-edge generative model work across AWS and on‑prem environments.

Qualifications

• 3-6 years of overall technical experience with 2 years in Generative AI and LLM technologies.
• 1+ years building agentic systems, workflow automation, or autonomous AI applications.
• Hands-on with agentic frameworks (AutoGen, LangGraph, CrewAI, Agency Swarm, or similar).
• Strong knowledge of workflow orchestration tools (Temporal, Airflow, Prefect).
• OpenAPI standards, A2A protocols, and Model Context Protocol (MCP) experience.
• Experience designing multi-agent architectures with memory, planning, and tool use.
• Proficiency in Python and ML/DL libraries; NLP knowledge.

Responsibilities

• Design, develop, and deploy multi-agent systems and agentic apps.
• Build intelligent workflow orchestration for autonomous decision-making.
• Implement A2A and MCP for seamless agent collaboration.
• Develop automation using OpenAPI standards for enterprise integration.
• Create self-healing, adaptive workflows optimizing business processes.
• Apply ML/DL and Generative AI tools for state-of-the-art solutions.
• Define best practices for scalable AI with Generative models and LLMs.
• Architect cloud-hosted Generative AI solutions and evaluate RAG workflows.
• Integrate agent-based systems and automation into applications with internal teams.
• Design IR for RAG with Vector DBs and Knowledge Graphs.
• Deploy LLMs on AWS and on-prem infrastructures; evaluate models for production.
• Stay updated on agentic AI, autonomy, and cutting-edge generative tech.

Skills

Generative AI

LLM technologies

Agentic systems

Workflow automation

OpenAPI

A2A protocols

MCP

RAG workflows

Cloud platforms

Python

System design

MLOps/LLMOps

Tools

Docker

Kubernetes

LangChain

LlamaIndex

LangGraph

AutoGen

CrewAI

Job description

Job Description

We are looking for a Senior Agentic AI Developer to design cutting-edge AI solutions and autonomous systems focused on agentic workflows and generative AI technologies. This position will be full-time and Hybrid Bengaluru.

What Youll Do

• Design, develop, and deploy multi-agent systems and agentic applications using frameworks like AutoGen, LangGraph, CrewAI, or similar
• Build intelligent workflow orchestration systems that enable autonomous decision-making and task execution
• Implement Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) for seamless agent collaboration
• Develop automation solutions using OpenAPI standards for integration with enterprise systems
• Create self-healing, adaptive workflows that optimize business processes autonomously
• Use ML, deep learning, and Generative AI tools to design, evangelize, and implement state-of-the‑art solutions
• Define and implement best practices for building, testing, and deploying scalable AI solutions, with a focus on generative models and LLMs using proprietary or open‑source models
• Drive successful business outcomes by designing and building cloud‑hosted Generative AI solutions
• Work closely with internal teams to integrate RAG workflows, agent‑based systems, and automation frameworks into applications
• Design and implement architectural solutions for Information Retrieval using RAG, Vector DBs, and Knowledge Graphs
• Work with public cloud (AWS) and on‑premises infrastructure for deploying LLMs, agents, and orchestration systems
• Evaluate, build, and fine‑tune ML models and LLMs to solve complex business problems
• Stay abreast of latest developments in agentic AI, autonomous systems, language models, and generative AI technologies

What You'll Need

Required:

• 3-6 years of overall technical experience with 2 years of hands‑on experience in Generative AI and LLM technologies
• 1+ years of experience building agentic systems, workflow automation, or autonomous AI applications
• Deep hands‑on experience with agentic frameworks (AutoGen, LangGraph, CrewAI, Agency Swarm, or similar)
• Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar)
• Expertise in OpenAPI standards, Agent-to-Agent (A2A) protocols, and Model Context Protocol (MCP)
• Experience designing multi‑agent architectures with memory, planning, and tool‑use capabilities
• Knowledge of agent evaluation, testing frameworks, and observability patterns
• Proven track record of deploying and optimizing LLM models for inference in production environments
• Extensive experience with LLM orchestration frameworks (LangChain, LlamaIndex required)
• Hands‑on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud‑based LLM platforms
• Expertise in RAG architectures, Fine‑tuning techniques, and Prompt Engineering
• Deep understanding of Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB) and Knowledge Graphs
• Expert in NLP techniques and deep learning libraries (Transformer models, LSTM, BiLSTM, CNN, BERT, GPT, T5)
• Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit‑learn
• Strong programming skills in Python (required), plus JavaScript/TypeScript or Node.js
• Deep understanding of data structures, algorithms, and system design patterns
• Hands‑on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving
• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for ML systems
• Knowledge of monitoring, logging, and observability tools for production AI systems

Preferred:

• Experience with function calling, tool use, and external API integration in agent systems
• Knowledge of reinforcement learning and agent training methodologies
• Familiarity with semantic reasoning, planning algorithms (ReAct, Chain-of-Thought, Tree-of-Thoughts)
• Experience with graph databases (Neo4j, Neptune) and ontology design
• Contributions to open‑source AI/ML projects
• Publications or patents in AI/ML domain