Agentic AI Developer

As an Agentic AI Developer, you will be responsible for designing, building, and deploying intelligent agents using frameworks like LangChain, OpenAI Agents SDK, or Google ADK. You will work on next-generation autonomous systems integrating LLMs, reasoning engines, and cloud-scale orchestration. Key Responsibilities: - Develop, test, and deploy Agentic AI systems using LangChain, OpenAI Agents SDK, or Google ADK. - Implement reasoning and planning workflows (ReAct, plan-act-observe loops). - Integrate external APIs, vector databases, and toolkits into agent frameworks. - Fine-tune and optimize open-source or proprietary LLMs for domain tasks. - Build and deploy MCP servers or custom agent tools. - Support CI/CD pipelines for AI model deployment. - Collaborate with data, DevOps, and product teams for smooth production rollout. Qualifications: - B-Tech - MCA In terms of essential skills, you should have expertise in: - Programming languages such as Python (primary), Node.js, or Go. - Agentic Frameworks including LangChain, OpenAI Agents SDK, or Google ADK. - LLM Ops covering prompt engineering, RAG, finetuning, quantization, optimization. - DevOps/MLOps practices like CI/CD, Docker, Kubernetes, MLflow, and Vertex AI Pipelines. - Model Serving using FastAPI, TorchServe, Vertex AI Endpoints. - Databases like Vector DBs such as Pinecone, FAISS, Weaviate. - Version Control systems like Git, GitHub Actions, Jenkins. Desired Skills: - Knowledge of distributed AI deployment tools like Ray, Hugging Face Accelerate. - Exposure to monitoring and observability tools such as Prometheus, Grafana. As an Agentic AI Developer, you will be responsible for designing, building, and deploying intelligent agents using frameworks like LangChain, OpenAI Agents SDK, or Google ADK. You will work on next-generation autonomous systems integrating LLMs, reasoning engines, and cloud-scale orchestration. Key Responsibilities: - Develop, test, and deploy Agentic AI systems using LangChain, OpenAI Agents SDK, or Google ADK. - Implement reasoning and planning workflows (ReAct, plan-act-observe loops). - Integrate external APIs, vector databases, and toolkits into agent frameworks. - Fine-tune and optimize open-source or proprietary LLMs for domain tasks. - Build and deploy MCP servers or custom agent tools. - Support CI/CD pipelines for AI model deployment. - Collaborate with data, DevOps, and product teams for smooth production rollout. Qualifications: - B-Tech - MCA In terms of essential skills, you should have expertise in: - Programming languages such as Python (primary), Node.js, or Go. - Agentic Frameworks including LangChain, OpenAI Agents SDK, or Google ADK. - LLM Ops covering prompt engineering, RAG, finetuning, quantization, optimization. - DevOps/MLOps practices like CI/CD, Docker, Kubernetes, MLflow, and Vertex AI Pipelines. - Model Serving using FastAPI, TorchServe, Vertex AI Endpoints. - Databases like Vector DBs such as Pinecone, FAISS, Weaviate. - Version Control systems like Git, GitHub Actions, Jenkins. Desired Skills: - Knowledge of distributed AI deployment tools like Ray, Hugging Face Accelerate. - Exposure to monitoring and observability tools such as Prometheus, Grafana.