The Agentic AI Engineer is responsible for designing, building, and deploying intelligent, AI agents capable of reasoning, planning, and executing complex tasks across business and technical domains. This role focuses on production‑grade agentic systems powered by Large Language Models (LLMs), integrated with enterprise tools, APIs, and data sources. This is a hands-on role requiring end‑to‑end ownership — from agent architecture and development through deployment, monitoring, evaluation, and continuous optimization.

The ideal candidate combines strong software engineering fundamentals with deep expertise in LLM application design, agent frameworks, Retrieval‑Augmented Generation (RAG), memory systems, and multi‑agent orchestration .

In addition to robust engineering skills, this role requires a product mindset—partnering with business stakeholders to shape use cases, select appropriate agentic tools and frameworks, and translate user needs into scalable technical solutions Key Responsibilities

Agent Architecture & Development

Design and implement agentic AI architectures, including:ReAct (Reason +Act)Plan‑and‑ExecuteTool‑using agentsMulti‑agent systems and coordinators





Build LLM‑powered applications using modern foundation modelsTranslate business use cases into reliable, scalable agent workflows with clear handoffs and fallbacks LLM & RAG Engineering

Develop and optimize prompt engineering strategies for reasoning, task execution, and tool use.

Implement

Retrieval‑Augmented Generation (RAG) pipelines using structured and unstructured data.Design and manage agent memory systems, including:

Short‑term (conversation/state) Long‑term (vector‑based memory)Work with vector databases Tooling, APIs & Integration

Build and integrate internal and external tools (APIs, microservices, enterprise systems).

Enable agents to safely interact with:

DatabasesBusiness applications

Automation platformsCloud services

Ensure robust error handling, retries, and fallback logic.

Production

Readiness & Operations

Deploy agentic systems into production environments.

Implement monitoring, logging, and evaluation frameworks for:Accuracy and task successLatency and cost efficiencySafety and policy complianceDesign and enforce guardrails to prevent hallucinations, unsafe actions, or data leakage.Continuously optimize system performance and cost

📌 Generative-AI Engineer (Agentic AI) (Maharashtra)
🏢 Yash Technologies
📍 Maharashtra