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RPA AI Architect

Shiro TechnologiesUnited States🇺🇸United StatesPosted Oct 2, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
Yesterday
MicroservicesSOAPAWSNLPAzureComputer VisionGenerative AIGoogle CloudKubernetesPythonREST

Job Description

We are seeking an experienced RPA AI Architect to design and lead enterprise-scale automation solutions combining RPA, AI/ML, Generative AI, intelligent agents, APIs, and workflow automation.

The role will focus on architecting and implementing intelligent automation solutions that improve business processes, operational efficiency, document processing, data extraction, decision-making, and end-to-end workflow automation across enterprise environments.

Key Responsibilities

Design end-to-end RPA, AI, and intelligent automation architectures for enterprise business processes.

Develop AI-powered automation solutions for document processing, data extraction, workflow automation, reporting, and business operations.

Architect solutions using RPA, LLMs, Generative AI, NLP, RAG, AI agents, and intelligent workflow orchestration.

Integrate automation solutions with enterprise applications, databases, APIs, SaaS platforms, and legacy systems.

Design and implement intelligent robotic/process automation workflows using RPA platforms, APIs, AI agents, and orchestration frameworks.

Develop scalable and reusable automation frameworks and enterprise automation standards.

Evaluate business processes and identify opportunities for RPA and AI-driven automation.

Establish secure, scalable, and highly available architectures for enterprise automation platforms.

Design appropriate access controls, authentication, monitoring, logging, and governance for automation solutions.

Evaluate and optimize AI models for accuracy, performance, reliability, relevance, and cost efficiency.

Lead architecture reviews, technical POCs, solution design, and production implementations.

Collaborate with business stakeholders, solution architects, data scientists, ML engineers, software engineers, DevOps, and security teams.

Provide technical leadership and architectural guidance throughout the automation lifecycle.

Required Skills

10+ years of experience in software engineering, RPA, AI/ML, enterprise architecture, or related technology.

Strong experience designing RPA, AI/ML, and Generative AI architectures.

Expertise in RPA, workflow automation, intelligent automation, and process orchestration.

Strong understanding of LLMs, NLP, RAG, embeddings, vector databases, and AI agents.

Experience with Python, REST APIs, microservices, and enterprise integration.

Hands-on experience with one or more RPA platforms such as UiPath, Automation Anywhere, or Microsoft Power Automate.

Experience with AWS, Azure, or Google Cloud Platform cloud platforms and AI services.

Experience integrating automation solutions with enterprise applications, databases, APIs, and SaaS platforms.

Strong understanding of automation architecture, scalability, monitoring, security, and governance.

Experience designing reusable automation frameworks and enterprise-level solutions.

Strong architecture documentation, presentation, and stakeholder communication skills.

Preferred Skills

Experience with UiPath, Automation Anywhere, or Power Automate.

Experience with LangChain, LangGraph, LlamaIndex, OpenAI, Azure OpenAI, AWS Bedrock, or equivalent technologies.

Experience with AI agents and agentic workflow automation.

Knowledge of RAG, Graph RAG, Knowledge Graphs, embeddings, and vector databases.

Experience with OCR, Intelligent Document Processing (IDP), computer vision, and document automation.

Experience integrating RPA platforms with REST APIs, SOAP APIs, databases, queues, and enterprise systems.

Experience with Azure Functions, AWS Lambda, serverless architecture, or equivalent technologies.

Experience with workflow/orchestration platforms and event-driven architectures.

Experience building human-in-the-loop AI and automation solutions.

Experience taking automation solutions from POC through production deployment and enterprise scale.

Knowledge of DevOps, CI/CD, containers, Kubernetes, and cloud-native architecture is a plus.

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