AI Engineer

About Us

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 industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall 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.

Job Description

• 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).

• 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.

• The Associate will define RAG success criteria (retrieval accuracy hallucination thresholds) and KPIs; inventory knowledge sources (documents databases) as an Enterprise Knowledge Base.

• Data sourcing plan and design end-to-end Agent flows covering triggers KB retrieval LLM calls and actions.

• 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.

• 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).

• Upon successful UAT the solution will be published to Production via the Production Control Room with BOT/Agent monitoring as part of Hypercare.

Qualifications

• Education: Bachelors or Masters in Computer Science AI/ML Data Science or equivalent practical experience.

• Experience: 1-3 years in software engineering; 1 years building AI-powered automation solutions in production.

• Certifications (Preferred): Cloud AI certifications (AWS Azure GCP); RPA certifications such as UiPath or Automation Anywhere.

• Scope & Growth Path: Implement designs under Senior Engineer guidance; progress toward independent stakeholder ownership.

Agentic AI

• Hands-on experience with LangChain LangGraph AutoGen or CrewAI.

• Core agent patterns: tool usage memory multi-step reasoning validation and guardrails.

• LLM APIs: OpenAI Anthropic Gemini or open-source models; structured prompt engineering.

RAG & Vector Infrastructure

• End-to-end RAG pipelines: ingestion chunking embedding vector stores and retrieval evaluation.

• Hands-on with vector databases; ability to diagnose and improve retrieval quality.

RPA

• Hands-on with UiPath Automation Anywhere or Microsoft Power Automate.

• Bot workflows with exception handling logging and enterprise system integrations.

Engineering

• Strong Python skills; experience with cloud AI services APIs data pipelines and event-driven systems.

Nice to Have

• Exposure to LoRA / QLoRA fine-tuning approaches.

• Agent observability and evaluation tooling such as LangSmith or Arize.

Responsibilities

• Build and maintain multi-agent workflows from solution design through production deployment.

• Implement root-cause analysis ERP/CRM/ITSM integrations and robust error handling.

• Design and operate end-to-end RAG systems; continuously monitor and improve retrieval quality.

• Develop and maintain RPA tasks; integrate AI agents with RPA and business logic.

• Write unit and integration tests; contribute to CI/CD pipelines and deployment automation.

• Collaborate with senior engineers; document pipelines agent configurations and operational runbooks.