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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: PythonJavaScriptSQLREST APIsHands-on experience with: UiPath and/or Microsoft Power AutomateExcel Macros and VBAOutlook AutomationDatabase integrationStrong understanding of: OCR technologiesAPI integration and mappingPrompt engineeringTool calling and structured outputsAI memory concepts and agent orchestrationExperience with: Git, Bitbucket, and DevOps practicesCI/CD pipelinesOAuth authenticationJSON/XML data formatsRelational 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: LangChainLangGraphAutoGenSemantic KernelCrewAIExperience with vector databases and AI search platforms such as: PineconeAzure AI SearchWeaviateExperience 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. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.