Software Engineer II - AI & Agentic Automation

Description 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.