AI Engineer

Automation Anywhere

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Vadodara, Gujarat, India1 – 3 Years Software Engineering (1+ Year in AI Production)1 month ago

RoleAI Engineer (Full-Stack Associate)

LocationVadodara, Gujarat, India

Experience1 – 3 Years Software Engineering (1+ Year in AI Production)

QualificationBachelor’s or Master’s in CS, AI/ML, or Data Science

Job Description

As an AI Engineer at Automation Anywhere, you will design, configure, and deploy AI Agents leveraging Retrieval-Augmented Generation (RAG) . You will be responsible for building the Enterprise Knowledge Base (EKB), defining chunking strategies, and fine-tuning models to ensure high retrieval accuracy. Your full-stack expertise will be used to integrate upstream APIs with downstream RPA Gen1, Gen2 (DocAI), and Gen3 (GenAI) bots to create a seamless end-to-end automation flow.
You will utilize core agent patterns—including tool usage, multi-step reasoning, and guardrails—to develop functional test prototypes. Working with LLMs like Gemini and GPT-4 , you will configure prompt templates and integrate downstream RPA tasks. From solution design and UAT deployment to production monitoring via the Control Room, you will ensure that AI-powered workflows are robust, scalable, and secure within the enterprise ecosystem.

Build and maintain multi-agent workflows from design through production.
Design and operate end-to-end RAG systems (ingestion, embedding, vector stores).
Integrate AI agents with RPA (UiPath/Automation Anywhere) and ERP/CRM systems.
Develop KB structures including data chunking, fine-tuning, and retrieval evaluation.
Prototype prompts and Agent flows covering triggers, LLM calls, and actions.
Implement root-cause analysis, logging, and robust error handling for bots.
Collaborate with senior engineers to document pipelines and operational runbooks.
Contribute to CI/CD pipelines and automated testing for GenAI solutions.

Education: Bachelor’s or Master’s degree in a technical field (CS, AI/ML).
Agentic AI: Hands-on experience with LangChain, LangGraph, or CrewAI .
LLMs: Proficiency in OpenAI, Anthropic, or Gemini APIs and prompt engineering.
RAG: Experience building RAG pipelines and working with vector databases.
RPA: Proficiency in Automation Anywhere, UiPath, or Microsoft Power Automate.
Engineering: Strong Python skills and experience with cloud AI services.
Preferred: Exposure to LoRA/QLoRA fine-tuning and LangSmith observability tools.

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