{"id":4057698,"url":"https://alion.io/job/workato-intern-software-engineering","title":"Intern, Software Engineering","company":{"id":58898,"name":"Workato","domain":"workato.com","url":"https://alion.io/company/workato","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":17,"ghost_share":0,"stale_share":0.588,"repost_share":0.118,"time_to_fill_p50_days":61,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"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":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Google Workspace","optional":false},{"name":"JavaScript","optional":false},{"name":"Jira","optional":false},{"name":"Least Privilege","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Ruby","optional":false},{"name":"Slack","optional":false},{"name":"GitHub","optional":true},{"name":"LLM","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-11-11T05:59:52Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T06:11:09Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About Workato\nWorkato is the leading Control and Execution Platform for Enterprise AI - the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 - including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors - Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com.\nWhy join us?\nUltimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking forteam players who want to actively build our company. \nBut, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. \nIf this sounds right up your alley, please submit an application. We look forward to getting to know you!\nAlso, feel free to check out why:\nBusiness Insider named us an “enterprise startup to bet your career on”\nForbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world\nDeloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America\nQuartz ranked us the #1 best company for remote workers\nResponsibilities\nWe’re looking for a motivated intern to join our integration and AI engineering team. You’ll design, build, and test MCP (Model Context Protocol) servers on the Workato platform, enabling AI assistants and agents to securely interact with enterprise systems such as CRMs, ticketing tools, HR platforms, and data warehouses. This is a hands-on role where you’ll ship real, working assets and learn how enterprise-grade agentic AI is built.\nIn this role, you will also be responsible to:\nBuild and configure MCP servers in Workato, exposing business capabilities as tools that AI clients (such as Claude) can call\n\nDevelop Workato recipes and skills that back each MCP tool, using connectors for systems like Salesforce, Slack, Jira, Google Workspace, and others\n\nWrite clear tool names, descriptions, and input/output schemas so AI models can select and use tools accurately\n\nTest MCP servers end to end with AI clients, and iterate based on tool-selection accuracy, error rates, and response quality\n\nImplement error handling, input validation, and logging to make tools reliable and debuggable\n\nApply security best practices, including least-privilege access, authentication, and handling of sensitive data\n\nUse Workato data tables, lookup tables, and connections appropriately to manage state and credentials\n\nDocument each MCP server (purpose, tools, authentication, example prompts, known limitations)\n\nParticipate in code and recipe reviews, team standups, and demos\n\nComplete a capstone project: design and deliver a production-ready MCP server for a real internal use case, and present it to the team\n\nRequired Qualifications\nCurrently pursuing or completed a Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field\n\nWorking knowledge of at least one programming or scripting language (Python, JavaScript, or Ruby preferred)\n\nUnderstanding of REST APIs, JSON, and basic HTTP concepts\n\nFamiliarity with core integration concepts: triggers, actions, data mapping, webhooks, and error handling\n\nBasic understanding of LLMs and AI assistants, and curiosity about how they use tools\n\nStrong problem-solving skills and attention to detail\n\nClear written communication, especially for documentation\n\nAbility to learn quickly and work independently with guidance\n\nPreferred Qualifications\nPrior exposure to Workato or another iPaaS or automation tool\n\nAwareness of the Model Context Protocol specification and its core concepts (tools, resources, prompts)\n\nExperience with OAuth 2.0, API keys, and secure credential handling\n\nFamiliarity with SQL or data transformation (formulas, mapping, JSON manipulation)\n\nExperience with prompt engineering or building LLM-powered projects\n\nFamiliarity with SaaS platforms such as Salesforce, Slack, Jira, or Google Workspace\n\nPersonal projects, hackathon work, or a GitHub portfolio showing integrations or automation\n\nWhat You’ll Learn\nEnterprise integration and orchestration patterns on Workato\n\nDesigning tools that AI agents can use reliably\n\nGovernance, security, and observability for agentic AI\n\nHow to take a prototype to a production-ready asset\n\nLogistics\nDuration: 6 months\n\nLocation: Chennai (Hybrid)\n\nCommitment: Full-time\n\nMentorship: Paired 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