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 agile 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.

📌 Senior Agentic AI Engineer / Agentic AI Architect (India)
🏢 Logic planet
📍 India