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The Software Engineer – AI & Agentic Automation is responsible for designing, developing, integrating, and deploying enterprise-grade Intelligent Automation and Agentic AI solutions. This role focuses on leveraging Agentic AI platforms, Large Language Models (LLMs), automation technologies, and enterprise systems to deliver scalable, secure, and high-impact automation solutions across Pearson business units.
The Software Engineer – AI & Agentic Automation is responsible for designing, developing, integrating, and deploying enterprise-grade Intelligent Automation and Agentic AI solutions. This role focuses on leveraging Agentic AI platforms, Large Language Models (LLMs), automation technologies, and enterprise systems to deliver scalable, secure, and high-impact automation solutions across Pearson business units.
Conduct feasibility studies and provide technical recommendations during the solution design phase.
Design and implement multi-agent workflows for autonomous task execution with Human-in-the-Loop (HITL) controls.
Create Solution Design Documents (SDDs) based on Process Definition Documents (PDDs).
Collaborate with business analysts and stakeholders to understand business processes, data standards, guidelines, and automation requirements.
Develop enterprise-grade Agentic AI solutions using LLMs, CrewAI, UiPath Agent Builder, Python, and REST APIs.
Build AI-powered assistants, conversational AI applications, and intelligent document processing solutions.
Design, develop, and deploy intelligent automation solutions using Microsoft Power Automate and UiPath.
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Integrate automation solutions with enterprise applications, APIs, databases, and third-party platforms.
Utilize AI-assisted development tools such as Claude, Cursor, and GitHub Copilot to improve development efficiency, testing, and code quality.
Implement secure API integrations, including OAuth authentication and data exchange using JSON and XML.
Configure and manage AWS environments to support Agentic AI platforms and application development.
Implement Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, or AWS CDK.
Work with relational databases such as SQL Server and PostgreSQL for data management and integration.
Develop evaluation frameworks, test strategies, and validation processes for AI and automation solutions.
Monitor production AI systems for performance, reliability, quality, and compliance.
Analyze incidents, identify root causes, and implement continuous improvements through prompt engineering, model optimization, and workflow enhancements.
Support CI/CD implementation and DevOps best practices throughout the development lifecycle.
Experience provisioning and managing AWS environments.
Knowledge of Infrastructure as Code (Terraform, AWS CloudFormation, AWS CDK).
Understanding of scalable, secure, and production-ready cloud architectures.
Bachelor's Degree in Computer Science, Engineering, Information Technology, or a related field.
Verified company details for this employer are not available yet.
Full-time
Mid
Hybrid
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