Software Engineer II 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

• Bachelors 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.