{"id":3346723,"url":"https://alion.io/job/cognira-software-engineer-intern-pfe-2027","title":"Software Engineer Intern - PFE 2027","company":{"id":3894456,"name":"Cognira","domain":"cognira.com","url":"https://alion.io/company/cognira","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Model Context Protocol","optional":false},{"name":"React.js","optional":false},{"name":"Storybook","optional":false},{"name":"TypeScript","optional":false},{"name":"AI Agents","optional":true},{"name":"ChatGPT","optional":true},{"name":"CI/CD","optional":true},{"name":"Claude","optional":true},{"name":"Function Calling","optional":true},{"name":"Gemini","optional":true},{"name":"Git","optional":true},{"name":"Go","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM","optional":true},{"name":"Nginx","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Python","optional":true},{"name":"Scala","optional":true},{"name":"SQL","optional":true},{"name":"Vite","optional":true}],"status":"live","first_seen_at":"2026-10-27T17:24:25Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-29T04:27:12Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About us:\nAt Cognira, we strongly believe that people are the biggest asset of our company. Our hand-picked team consists of passionate, collaborative, and forward-thinking individuals from all over the globe. We are passionate about making science easy and accessible to retailers, helping them get more value from people, data, and systems. We bring together expertise in retail, science, and scalable technologies to automate and enhance the quality of decision-making through software and consulting services.\nWe are proud to have a growing team of domain experts and data scientists, as well as a culture that fosters strong and long-lasting relationships with our clients.\nOur Locations:\nAtlanta, GA, US \nTunis, Tunisia\nIstanbul, Turkey\nParis, France\nPorto, Portugal\nOur values:\nBe nice and trustworthy\nPut our customers first\nSucceed together\nNever stop improving\nAre you ready to grow with us?To find out more about Cognira, please visit our website at www.cognira.com\nPlease submit your resume in English.\nI- Frontend Team Internship Topics:\nTopic1 : A Visual Screen Builder with AI-Ready Design Handoff\nProject Overview:\nCognira's design system is documented in Storybook, but Product Managers and UX designers currently require engineering support to assemble screens using available components. Additionally, design handoff between design and engineering teams remains a manual and error-prone process.\nThis project will create a visual screen builder that allows non-technical users to construct screens from existing Storybook components, generate structured specifications, and expose those specifications to AI coding agents through an MCP server.\nDeliverables\nScreen Builder Application\nComponent catalog automatically generated from Storybook metadata.\nVisual canvas for building screens using predefined layouts.\nAuto-generated property editor based on TypeScript component definitions.\nSave and load functionality for screen configurations.\nScreen Specification Framework\nJSON Schema automatically generated from component prop definitions.\nValidation of screen specifications against generated schemas.\nHuman-readable and AI-readable Markdown exports.\nMCP Integration\nAn MCP server that exposes screen specifications to AI coding agents.\nSupport for AI-powered validation and implementation using approved components and properties.\nRequired Skills\nTypeScript and React\nFront-end application development\nJSON and schema design\nUnderstanding of component-based design systems\nProblem-solving and software architecture skills\nPreferred Skills\nStorybook\nMCP (Model Context Protocol)\nTypeScript metadata and code generation\nDesign systems and UX workflows\nAI-assisted development tools\nAPI and server development\nTopic2: Interactive MCP Apps for PromoAI's Agent Cora\nProject Overview\nPromoAI is a SaaS platform that helps retailers plan, forecast, and analyze promotional performance. Its AI assistant, Cora, answers business users' questions in natural language, helping them understand forecasts, identify promotion conflicts, and gain insights into their promotional activities.\nCora can already be accessed through AI applications such as Claude using the Model Context Protocol (MCP), but responses are currently delivered as plain text. MCP Apps, a recent extension to the protocol, allow tools to return interactive web applications directly within AI chat experiences.\nIn this project, you will enhance Cora's user experience by building interactive MCP Apps that allow users to explore charts, sort and export tables, select products and stores, and interact with forecast data directly from their AI assistant. You'll work across both a TypeScript backend and a modern web frontend while validating the experience across multiple AI platforms.\nDeliverables\nImplement MCP Apps support within Cora's MCP server, providing interactive experiences alongside text-based responses for clients that do not support MCP Apps.\nDevelop a library of reusable interactive views, including:Answer cards with charts and data tables\nPromotion and event information cards\nForecast breakdown visualizations\nPromotions calendar views\n\nBuild interactive components that communicate directly with backend services, including:Product and store pickers\nAlerts inbox\nExportable data tables\n\nImplement adaptive styling that follows the theme of each host AI application in both light and dark modes.\nCreate automated tests covering both frontend components and backend server changes.\nProduce a compatibility report for Claude, ChatGPT, Gemini, and VS Code.\nStretch Goal: Develop a shared component library that can be used across both Cora's internal chat interface and external AI applications.\nRequired Skills\nWeb Development\nTypeScript / JavaScript\nReact\nVite\nNginx\nFundamental Knowledge\nLLM tool calling\nAI agents\nModel Context Protocol (MCP)\nAutomated testing\nPreferred Skills\nPython development\nWeb security fundamentals, including iframes, Content Security Policy (CSP), and OAuth\nBuilding interactive charts and data tables for web applications\nUI component design and frontend performance optimization\nII- Backend Team Internship Topics:\nTopic 1: Test-Impact Selection Service\nProject Overview\nCurrently, every code change triggers the entire test suite, even when only a small portion of the codebase is affected. This project aims to build an intelligent test-selection service that analyzes code changes, determines impacted areas, and executes only the relevant tests while providing clear explanations for each selection.\nDeliverables\nBuild a service that identifies and executes tests affected by a code change.\nProvide explanations showing why each test was selected.\nGenerate replay reports using historical commits to demonstrate reduced testing time without missed failures.\nIntegrate the solution into the CI/CD pipeline.\nDeliver technical documentation and a final project demonstration.\nRequired Skills\nScala\nSoftware testing fundamentals\nObject-oriented programming\nGit\nPreferred Skills\nPostgreSQL\nSemanticDB\nCI/CD pipelines\nStatic code analysis\nSoftware architecture and dependency analysis\nTopic 2: Human-in-the-Loop AI Development Assistant\nProject Overview\nAs AI-generated code becomes increasingly common, developers need tools that provide visibility, review capabilities, and human oversight throughout the development process.\nThis project focuses on building a full-stack application that enables developers to review AI-generated code changes, request explanations, collaborate on reviews, and maintain control over AI-assisted development workflows.\nDeliverables\nBuild a web application for reviewing AI-generated code changes.\nEnable developers to comment on specific code blocks.\nAllow users to request explanations and clarifications for generated code.\nProvide pull-request walkthrough capabilities.\nCreate a collaborative review experience that combines AI assistance with human validation.\nDeliver documentation and a final demonstration.\nRequired Skills\nFull-stack web development\nReact\nSQL databases\nSoftware engineering fundamentals\nGit and collaborative development workflows\nPreferred Skills\nGo or Python\nPostgreSQL\nAI-assisted development tools\nLarge Language Models (LLMs)\nCode review and developer productivity 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