{"id":3164675,"url":"https://alion.io/job/jones-lang-lasalle-software-engineer-i","title":"Software Engineer I","company":{"id":616,"name":"Jones Lang LaSalle","domain":"jll.com","url":"https://alion.io/company/jones-lang-lasalle","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":493,"ghost_share":0.004,"stale_share":0.087,"repost_share":0.039,"time_to_fill_p50_days":7,"computed_at":"2026-10-25T05:49:26Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":8000,"max_usd":22000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":36},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C#","optional":false},{"name":"ChatGPT","optional":false},{"name":"Claude","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"React.js","optional":false},{"name":"SQL","optional":false},{"name":"State Management","optional":false},{"name":"TypeScript","optional":false},{"name":"WordPress","optional":false},{"name":"ASP.NET Core","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Copilot","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"GitHub","optional":true},{"name":"Jest","optional":true},{"name":"MySQL","optional":true},{"name":"PHP","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redux","optional":true},{"name":"styled-components","optional":true},{"name":"Tailwind CSS","optional":true},{"name":"Zustand","optional":true}],"status":"live","first_seen_at":"2026-10-22T00:00:00Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-25T13:20:12Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"JLL empowers you to shape a brighter way.\nOur people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.\nAbout the Role\nAs a Software Engineer I on the Martech Intelligence Pod, you'll be starting your engineering career working on real customer-facing applications across both frontend and backend, learning the foundations of professional software development in a supportive environment. You'll also have the opportunity to explore and learn about AI tools and AI-centric solutions that are becoming central to how we build products.\nYour primary focus will be maintaining and improving the customer-facing websites we host while gradually learning about infrastructure and integration challenges the Intelligence Pod tackles. Importantly, you'll also have dedicated time to explore AI tools, experiment with LLM APIs, understand how agents work, and think about where AI can solve problems better than traditional approaches.\nThis is a structured onboarding role: you'll work closely with senior engineers who will mentor you through the full development lifecycle - from understanding requirements, to writing frontend components and backend services, to testing, debugging, and deploying to production. You'll start with well-scoped, low-risk tasks on both frontend and backend, and gradually take on more responsibility as you gain confidence and expertise. You'll also spend time experimenting with AI tools, building small proof-of-concepts, and learning how modern AI capabilities can be integrated into applications.\nThe role demands intellectual curiosity, a willingness to ask questions, and genuine interest in learning how real systems work - both traditional software and AI-powered systems. Success is measured by your growth as a full-stack engineer, the quality of code you write, your reliability, your ability to communicate what you're learning, and your engagement with exploring AI as a tool and mindset. This is a fully-supported entry point into professional full-stack software engineering at a global scale, with exposure to cutting-edge AI capabilities.\nWho You Are\nWe're optimizing for learning potential, solid fundamentals, and genuine engagement with engineering. You don't need years of experience - you need to be curious, humble about what you don't know, and eager to grow.\nYou have a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent bootcamp/self-taught experience with a portfolio demonstrating competency\nYou are proficient in English, both written and verbal, sufficient for success in a remote and largely asynchronous work environment\nYou have 0-2 years of professional software engineering experience, or are a recent graduate with solid foundational knowledge\nYou have hands-on experience writing code in C# or Java (through academic projects, bootcamp, or personal projects) and understand the basics of how programs work\nYou have some experience with React and TypeScript or are eager to learn them quickly - through academic projects, bootcamp, tutorials, or personal projects; you understand the basics of components and JSX\nYou know the basics of HTML, CSS, and JavaScript - you understand how the browser works and can build simple web pages and interactive elements\nYou understand the fundamentals of object-oriented programming: classes, objects, inheritance, and interfaces\nYou can debug code in multiple environments: backend (logs, IDE debugger) and frontend (browser developer tools, console logs)\nYou've written code that other people have read and reviewed - you're comfortable receiving feedback and iterating\nYou know the basics of relational databases and can write simple SQL queries (SELECT, INSERT, UPDATE); you're learning to think about data\nYou've worked with Git and understand the basics of version control, branching, and merging\nYou can debug code systematically: read error messages, add logging, trace through code, form hypotheses about what's wrong\nYou're genuinely curious about how things work and you ask good questions when you don't understand something\nYou're interested in and curious about AI tools (LLMs, generative AI, agents) - you've probably experimented with ChatGPT, Claude, or similar tools and think about how they could be useful\nYou're open to exploring AI-centric solutions to problems and willing to experiment with new approaches that leverage AI capabilities\nYou can explain what you've learned in writing: you're comfortable documenting decisions, asking for help in PRs, and sharing what you discovered\nYou're reliable and follow through: you finish what you start, communicate when you're blocked, and ask for help before getting stuck for too long\nYou're humble about what you don't know and genuinely want to learn from more experienced engineers\nYou make an effort to include others and appreciate feedback as a gift, not a criticism\nWhat You'll Do\nLearning & Foundational Work:\nWork on small, well-scoped tasks with clear acceptance criteria: bug fixes, simple feature additions, documentation improvements (both frontend and backend)\nGet hands-on with the tools and technologies we use: C#/Java backend, React/TypeScript frontend, SQL, Git, our test frameworks, our deployment processes\nLearn how our customer-facing applications work: what AEM is, how WordPress sites are structured, how they serve customers, how frontend and backend work together\nUnderstand the full development lifecycle: from understanding a requirement, to writing code (frontend components and backend services), to testing, to deploying to production with safety\nFrontend Development:\nFix simple bugs in our React/TypeScript applications: layout issues, component state problems, missing features\nImplement small features: simple forms, content displays, UI improvements requested by stakeholders\nLearn React fundamentals: components, hooks, props, state management\nDebug frontend issues using browser developer tools: understand CSS problems, trace JavaScript execution\nHelp improve frontend test coverage: write simple unit tests for components\nLearn how to consume backend APIs from the frontend: understand requests, responses, error handling\nBackend Development:\nHelp fix bugs in our C# or Java backend services: simple issues with clear reproduction steps\nImplement small backend features: API endpoints, database queries, business logic\nLearn backend fundamentals: how services are structured, how databases work, how to handle errors\nDebug backend issues: read logs, understand stack traces, trace through code\nHelp improve test coverage: write simple unit and integration tests\nLearn how different systems connect: understand what the Intelligence Pod builds\nCustomer-Facing Site Support:\nHelp maintain and support http://jll.com (AEM) and WordPress installations - responding to issues, fixing bugs, implementing small improvements\nParticipate in code review: both receiving feedback on your code and reviewing code from peers (with guidance)\nHelp with code maintenance: refactoring simple code, improving documentation, reducing technical debt\nLearning Infrastructure & Integration Concepts:\nObserve and help with integration work: understand how we connect to external systems, why these connections are fragile, how errors are handled\nLearn what the broader Intelligence Pod does: building MCPs, working with agents, connecting marketing systems together\nAsk questions and document what you learn: you're building your mental model of how these systems work\nAI Exploration & Learning:\nDedicate time to learning and experimenting with AI tools: LLM APIs (Claude, GPT, etc.), prompt engineering, understanding how agents work\nBuild small personal projects and proof-of-concepts using AI: tools that solve real problems, experiments that help you understand AI capabilities and limitations\nExplore how AI can be integrated into our applications: think about where AI could improve user experience, automate tasks, or unlock new capabilities\nLearn about agent systems, multi-step reasoning, and tool use: understand what the Intelligence Pod is building and why\nDocument your experiments and learnings: write up what you tried, what worked, what didn't, and what you discovered\nParticipate in code reviews and discussions about AI-centric solutions: understand how senior engineers think about AI architecture and tradeoffs\nStay current on AI developments: follow announcements, experiment with new models/tools, and bring ideas back to the team\nDevelopment Practices:\nWrite tests for code you write: unit tests on both frontend and backend, simple integration tests\nDeploy code to production (with a more experienced engineer watching/guiding the first few times)\nDebug production issues under mentorship: learn to read logs, understand error messages, trace through systems\nParticipate in on-call rotation for customer-facing applications: responding to issues, escalating when needed\nGrowing Your Skills:\nLearn from code review: understand why experienced engineers structure code certain ways, ask questions about their decisions\nPair program with senior engineers: watch how they debug, design, and think through problems on both frontend and backend\nWork on increasingly complex tasks as you gain confidence: from bug fixes, to small features, to contributing to larger pieces of infrastructure work\nContribute to improving our team: documentation, test coverage, code clarity, processes that make everyone more effective\nCommunication & Collaboration:\nWrite clear commit messages and PR descriptions\nAsk questions in team channels when you're stuck - don't wait until you're frustrated\nCommunicate regularly with your mentors about what you're learning, where you're struggling, and what you want to focus on next\nHelp teammates when you can: testing code, reviewing docs, asking clarifying questions\nNice to Have\nAcademic or bootcamp projects demonstrating full-stack fundamentals (both frontend and backend)\nExperience with Git, GitHub, or similar version control in a team setting\nFamiliarity with frontend testing frameworks (Jest, React Testing Library) or backend testing frameworks\nExperience with databases (PostgreSQL, MySQL) beyond just basic SQL\nExposure to state management in React (Context API, Redux, Zustand, etc.)\nExposure to CSS frameworks or CSS-in-JS libraries (Tailwind, styled-components, etc.)\nExposure to backend frameworks or libraries (http://ASP.NET , Spring, etc.)\nExposure to cloud platforms (AWS, GCP, Azure) or containerization (Docker)\nInterest in marketing technology, content management systems, or enterprise software\nExperimentation with AI tools (ChatGPT, Claude, GitHub Copilot, etc.) or interest in learning about LLMs\nPersonal projects or experiments using AI APIs or tools\nUnderstanding of or curiosity about agent systems, prompt engineering, or generative AI\nOpen source contributions or a GitHub profile showing projects you've worked on\nLocation:\nOn-site -Bengaluru, KAScheduled Weekly Hours:\n40If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements. We’re interested in getting to know you and what you bring to the table!\nAt JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. 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