Senior Agentic AI Engineer / Agentic AI Architect

Logic Planet; India; Hybrid; INR 350,000 - 550,000; Full time

Job summary

Logic Planet is seeking an experienced Agentic AI Engineer/Architect to design, develop, and scale next‑generation AI solutions powered by Large Language Models (LLMs), Generative AI, and multi‑agent architectures. You will lead architecture, implementation, and deployment of enterprise‑grade agentic capabilities.

The role emphasizes agent orchestration, RAG systems, reasoning frameworks, and AI workflow automation, with hybrid/remote work options and collaboration across product, data science,

Qualifications

• 5+ years in AI/ML, with 2+ years in Generative AI and LLM-based systems.
• Experience with agent orchestration and advanced RAG systems.
• Familiarity with LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.

Responsibilities

• Design and develop production-grade Agentic AI solutions leveraging LLMs, Generative AI, and autonomous multi-agent systems.
• Architect end-to-end AI workflows involving planning, reasoning, tool usage, memory management, orchestration, and automation.
• Build scalable AI agent ecosystems enabling collaborative decision-making and autonomous execution.
• Design agent communication frameworks using A2A patterns and Model Context Protocol (MCP).
• Develop hybrid retrieval systems with vector and keyword search, metadata filtering, and contextual retrieval.
• Create knowledge graph-enabled retrieval and reasoning to boost accuracy and explainability.
• Develop multi-agent workflows with LangGraph, LangChain, CrewAI, AutoGen or similar.
• Implement workflow automation integrating enterprise systems, APIs, databases, and business processes.
• Build multimodal capabilities across text, documents, images, audio, and structured data.
• Integrate agents with Azure AI Foundry, Vertex AI Studio, OpenAI, Anthropic, and similar ecosystems.
• Deploy AI solutions in cloud environments (Azure, GCP, AWS) and build reusable AI infrastructure.

Job description

Job Title: Senior Agentic AI Engineer / Agentic AI Architect

Hybrid / Remote

Experience

5+ Years in AI/ML, with 2+ Years in Generative AI and LLM-based Systems

Job Summary

We are seeking an experienced and innovative Agentic AI Engineer/Architect to design, develop, and scale next-generation AI solutions powered by Large Language Models (LLMs), Generative AI, and multi-agent architectures. The ideal candidate will have deep expertise in agent orchestration, advanced RAG systems, reasoning frameworks, and AI workflow automation.

You will play a key role in defining and implementing enterprise-grade Agentic AI capabilities, leveraging cutting-edge frameworks and platforms to solve complex business challenges through intelligent, autonomous systems.

Key Responsibilities

Agentic AI Architecture & Development

• Design and develop production-grade Agentic AI solutions leveraging LLMs, Generative AI, and autonomous multi-agent systems.
• Architect and implement end-to-end AI workflows involving planning, reasoning, tool usage, memory management, orchestration, and task automation.
• Build scalable AI agent ecosystems capable of collaborative decision-making and autonomous execution.
• Design robust agent communication frameworks using Agent-to-Agent (A2A) patterns and Model Context Protocol (MCP).

Advanced RAG & Knowledge Systems

• Design and implement advanced Retrieval-Augmented Generation (RAG) architectures.
• Develop hybrid retrieval systems combining vector search, keyword search, metadata filtering, reranking, and contextual retrieval techniques.
• Build knowledge graph-enabled retrieval and reasoning systems to enhance accuracy and explainability.
• Establish evaluation frameworks for retrieval quality, hallucination reduction, agent performance, and end-user effectiveness.

Multi-Agent & Workflow Orchestration

• Develop sophisticated multi-agent workflows using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar technologies.
• Design agent orchestration layers supporting dynamic routing, delegation, collaboration, reflection, and iterative reasoning.
• Implement workflow automation solutions integrating enterprise systems, APIs, databases, and business processes.

Multimodal AI Development

• Build multimodal AI capabilities across text, documents, images, audio, and structured datasets.
• Develop intelligent document processing, image understanding, summarization, classification, and conversational AI applications.
• Integrate multimodal foundation models into enterprise workflows and agent ecosystems.

Platform Integration & Deployment

• Integrate AI agents with platforms such as Microsoft Copilot Studio, Azure AI Foundry, Vertex AI Studio, OpenAI, Anthropic, and other AI ecosystems.
• Deploy and manage AI solutions in cloud environments including Azure, GCP, and AWS.
• Build APIs, services, and reusable AI infrastructure components for enterprise adoption.

Optimization & Governance

• Optimize prompt engineering strategies, retrieval performance, agent reasoning quality, and LLM effectiveness.
• Monitor, evaluate, and improve latency, accuracy, reliability, and cost efficiency of AI systems.
• Establish best practices around scalability, security, observability, governance, responsible AI, and compliance.
• Design monitoring frameworks for agent behavior, model drift, performance tracking, and operational excellence.

Cross-Functional Collaboration

• Partner with Product Managers, Engineering teams, Data Scientists, and Business Stakeholders to define AI use cases and solution roadmaps.
• Translate business requirements into scalable Agentic AI architectures.
• Mentor team members and drive AI engineering best practices across the organization.