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Senior Agentic AI Developer

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Hybrid

Senior Agentic AI Developer

Cai Info India

Senior Agentic AI Developer

Skills

Deep LearningDockerReactNodeTypescriptPythonPyTorchTensorFlowNeo4jSwagger/OpenAPIMachine LearningAIAWSKubernetesNo-code AutomationsNLP / Natural Language ProcessingApache AirflowJavascript

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹3,000,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

14 September 2026

What they need


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

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