Sr. AI Engineer

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<p><b><span>About Us</span></b></p><p></p><p><span>Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.</span></p><h2>Job Description</h2><ul><li><p>We are looking for a full-stack associate to design, configure, and deploy AI Agents and intelligent automation solutions on an enterprise-grade Automation Anywhere GenAI platform while leveraging RAG (Retrieval-Augmented Generation) as the knowledge foundation for the Automation Anywhere Enterprise Knowledge Base (EKB).</p></li><li><p>Full-stack knowledge of candidate will be used to integrate upstream full stack bots/APIs and downstream AAA Enterprise RPA Gen1, Gen2 (DocAI), and Gen3 (GenAI) bots, and vice versa.</p></li><li><p>The Associate will define RAG success criteria (retrieval accuracy, hallucination thresholds) and KPIs; inventory knowledge sources (documents, databases) as an Enterprise Knowledge Base.</p></li><li><p>Data sourcing plan and design end-to-end Agent flows covering triggers, KB retrieval, LLM calls, and actions.</p></li><li><p>KB structure (chunking, fine-tuning) will be defined and built using EKB. Prototype prompts and Agents will be developed to produce functional test Chat/Agent prototypes.</p></li><li><p>Agents and Prompts will be configured with a selected LLM (Gemini/GPT-4) to generate Agent configurations and prompt templates. Downstream API tasks (RPA steps/external calls) will be integrated, followed by UAT deployment (publish Agent/KB).</p></li><li><p>Upon successful UAT, the solution will be published to Production via the Production Control Room, with BOT/Agent monitoring as part of Hypercare.</p></li></ul><p></p><h2>Qualifications</h2><ul><li><p>Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or equivalent practical experience.</p></li><li><p><b><u>Experience: 1-3 years in software engineering; 1+ years building AI-powered</u></b> automation solutions in production.</p></li><li><p>Certifications (Preferred): Cloud AI certifications (AWS, Azure, GCP); RPA certifications such as UiPath or Automation Anywhere.</p></li><li><p>Scope & Growth Path: Implement designs under Senior Engineer guidance; progress toward independent stakeholder ownership.</p></li></ul><p></p><h2>Agentic AI</h2><ul><li><p>Hands-on experience with LangChain, LangGraph, AutoGen, or CrewAI.</p></li><li><p>Core agent patterns: tool usage, memory, multi-step reasoning, validation and guardrails.</p></li><li><p>LLM APIs: OpenAI, Anthropic, Gemini, or open-source models; structured prompt engineering.</p></li></ul><p></p><h2>RAG & Vector Infrastructure</h2><ul><li><p>End-to-end RAG pipelines: ingestion, chunking, embedding, vector stores, and retrieval evaluation.</p></li><li><p>Hands-on with vector databases; ability to diagnose and improve retrieval quality.</p></li></ul><p></p><h2>RPA</h2><ul><li><p>Hands-on with UiPath, Automation Anywhere, or Microsoft Power Automate.</p></li><li><p>Bot workflows with exception handling, logging, and enterprise system integrations.</p></li></ul><p></p><h2>Engineering</h2><ul><li><p>Strong Python skills; experience with cloud AI services, APIs, data pipelines, and event-driven systems.</p></li></ul><p></p><h2>Nice to Have</h2><ul><li><p>Exposure to LoRA / QLoRA fine-tuning approaches.</p></li><li><p>Agent observability and evaluation tooling such as LangSmith or Arize.</p></li></ul><p></p><h2>Responsibilities</h2><ul><li><p>Build and maintain multi-agent workflows from solution design through production deployment.</p></li><li><p>Implement root-cause analysis, ERP/CRM/ITSM integrations, and robust error handling.</p></li><li><p>Design and operate end-to-end RAG systems; continuously monitor and improve retrieval quality.</p></li><li><p>Develop and maintain RPA tasks; integrate AI agents with RPA and business logic.</p></li><li><p>Write unit and integration tests; contribute to CI/CD pipelines and deployment automation.</p></li><li><p>Collaborate with senior engineers; document pipelines, agent configurations, and operational runbooks.</p></li></ul><p></p><p style="text-align:inherit"></p><div><div><div><div><p style="text-align:left"><span>All unsolicited resumes submitted to any <span><span><span><span><span><span><span><span><span><span><span><span class="WEM0"><span style="overflow-wrap: break-word; display: inline; text-decoration: inherit; hyphens: auto;">@automationanywhere.com</span></span></span></span></span></span></span></span></span></span></span></span></span> email address, whether submitted by an individual or by an agency, will not be eligible for an agency fee.</span></p></div></div></div></div>

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