Role: AI/ML Developer – Agentic AI & Workflow Automation

Experience: 5–7 Years About the Role

We are seeking an experienced AI/ML Developer with robust expertise in Agentic AI and workflow automation. The ideal candidate will have hands-on experience designing, building, and deploying production-ready AI agents that automate real-world business processes. This role involves developing single-agent and multi-agent systems that are scalable, reliable, observable, and cost-efficient.

You should be comfortable translating loosely defined business problems into practical AI-driven solutions while understanding where agentic AI is the right approach—and where traditional solutions are more appropriate. Key Responsibilities

Design, develop, and deploy agentic AI systems to automate business workflows, including customer service, operations, document processing, and internal business applications.

Build and integrate Model Context Protocol (MCP) servers and clients to enable AI agents to securely interact with enterprise tools, data sources, and internal systems.

Design and implement multi-agent architectures, including orchestration, task delegation, inter-agent communication, and failure handling.

Own context engineering by developing effective prompts, retrieval strategies, context window management, memory architecture (short-term and long-term), and token/cost optimization.

Develop Retrieval-Augmented Generation (RAG) pipelines where appropriate and understand when retrieval-based approaches are not required.

Evaluate, monitor, and improve agent performance through testing, tracing, evaluation frameworks, and observability tools to detect drift and failures.





Collaborate with business stakeholders to identify automation opportunities and translate business requirements into scalable agentic AI solutions with measurable outcomes.

Stay current with emerging trends, frameworks, and technologies within the Agentic AI ecosystem, making practical build-versus-buy recommendations.

Required Skills & Experience

Approximately 5–7 years of overall software engineering or machine learning experience, including 1.5–2+ years of hands-on experience developing LLM-powered and agentic AI systems.

Strong understanding of Generative AI concepts, including Large Language Models (LLMs), prompt engineering, sampling strategies, function/tool calling, structured outputs, and common failure modes.

Practical experience building or integrating Model Context Protocol (MCP) servers and exposing tools and resources for AI agents.

Hands-on experience with agentic AI frameworks such as LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or equivalent custom orchestration frameworks.

Experience designing and implementing multi-agent systems, including supervisor-worker patterns, agent handoffs, shared state management, and conflict resolution.

Strong knowledge of context engineering, including prompt architecture, context window optimization, summarization strategies, memory design, and RAG implementation.

Excellent programming skills in Python (experience with TypeScript/Node.js is an advantage).

Strong experience with REST APIs, backend development, and software engineering best practices.

Experience working with one or more major LLM platforms, including OpenAI, Anthropic Claude, Google Gemini, or open-source models deployed using vLLM or Ollama.

Experience implementing evaluation and observability frameworks using tools such as LangSmith, Langfuse, Arize, or custom tracing solutions.

📌 Agentic AI Developer (Noida)
🏢 Dipole Group
📍 Noida