Overview

Urgent Hiring: - Agentic AI Engineer Multi Ops IT Solutions — Build the next generation of autonomous AI systems Location: IT Park, Chandigarh Company: MultiOps IT Solutions Experience: 3-5 Years

Responsibilities

• Design and build end-to-end Agentic AI systems with planning, memory, and multi-step reasoning capabilities
• Develop and manage MCP (Model Context Protocol) driven architectures and tool-use pipelines
• Implement RAG (Retrieval-Augmented Generation) systems using vector databases such as Pinecone, Deviate, or vector
• Integrate multi-model AI solutions across OpenAI, Anthropic Claude, Google Gemini, and open-source LLMs
• Build robust orchestration logic with fallback strategies, guardrails, and observability hooks
• Develop APIs and backend services in Python / Node.js to support AI-powered workflows
• Deploy and monitor production AI systems on AWS, Azure, or GCP with a focus on reliability and scale
• Ensure AI explainability, security, and responsible deployment practices across all solutions

Qualifications

• About the role
• We are actively looking for a passionate Agentic AI Engineer who thrives at the frontier of autonomous AI systems. You will design and deploy intelligent agents that plan, reason, and act — integrating multi-model pipelines, orchestration frameworks, and real-world tool usage. If you are obsessed with agentic architectures, MCP, RAG, and making AI systems that actually do things, this role is for you.
• 3–5 years of hands-on experience in AI/ML engineering, with a strong focus on LLMs and generative AI
• Solid understanding of agentic design patterns — React, Chain-of-Thought, tool-calling, multi-agent collaboration
• Proficiency in Python; familiarity with LangChain, LlamaIndex, AutoGen, CrewAI, or similar agent frameworks
• Experience building and consuming REST APIs, microservices, and event-driven architectures
• Working knowledge of prompt engineering, fine-tuning strategies, and model evaluation techniques
• Familiarity with AI observability tools (LangSmith, Helicone, Weights & Biases, etc.)
• Understanding of CI/CD pipelines and DevOps practices for AI systems
• MCP / Tool-use, RAG Pipelines, Vector Databases, AI Orchestration, Multi-agent Systems, LangChain / LlamaIndex, Prompt Engineering, AI Observability, LSTM / Seq2SeqGuardrails / Safety OpenAI / Claude / Gemini APIs, AWS / Azure / GCP
• Cutting-edge AI work
• Real-world impact
• Strong career growth
• Collaborative culture