Software Engineer III - AI & Agentic Automation

Software Engineer – AI & Agentic Automation

Role Overview

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.

Key Responsibilities

Solution Design & Architecture

• 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.

AI & Agentic Automation Development

• 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.
• 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.

Integration & Platform Engineering

• 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.

Testing, Monitoring & Continuous Improvement

• 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.

Required Skills & Experience

Technical Skills

• Strong experience in: 
  • Python
  • JavaScript
  • SQL
  • REST APIs
• Hands-on experience with: 
  • UiPath and/or Microsoft Power Automate
  • Excel Macros and VBA
  • Outlook Automation
  • Database integration
• Strong understanding of: 
  • OCR technologies
  • API integration and mapping
  • Prompt engineering
  • Tool calling and structured outputs
  • AI memory concepts and agent orchestration
• Experience with: 
  • Git, Bitbucket, and DevOps practices
  • CI/CD pipelines
  • OAuth authentication
  • JSON/XML data formats
  • Relational databases (SQL Server, PostgreSQL)

Cloud & Infrastructure

• 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.

Nice-to-Have Skills

• Experience with Microsoft Copilot Studio.
• Knowledge of Model Context Protocol (MCP) and agent interoperability.
• Experience with AI frameworks such as: 
  • LangChain
  • LangGraph
  • AutoGen
  • Semantic Kernel
  • CrewAI
• Experience with vector databases and AI search platforms such as: 
  • Pinecone
  • Azure AI Search
  • Weaviate
• Experience building multi-agent or Agentic AI systems in enterprise environments.

Education

• Bachelor's Degree in Computer Science, Engineering, Information Technology, or a related field.

Soft Skills

• Strong analytical and problem-solving capabilities.
• Excellent communication and technical documentation skills.
• Ability to collaborate effectively with business and technology stakeholders.
• Strong organizational and project management skills.
• Ability to thrive in Agile/Scrum and fast-paced delivery environments.
• Proactive mindset with a passion for innovation, AI, and automation.