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.
