New opportunity

Software Engineer II (FullStack-NodeJS, VueJS/ReactJS) - AI/ML

FactSet · Hyderabad, India

About this role

FactSet is seeking a Software Engineer II to join the newly formed AI Foundry - Platform Engineering team. This role focuses on designing and developing AI tools, workflows, and agents that form the foundation of an agentic system for financial intelligence. You will work in a high-visibility, strategic organization to architect and scale AI capabilities across the enterprise. Responsibilities include developing high-quality, maintainable code, collaborating with a geographically diverse team, following best practices in code reviews and documentation, and providing technical support. Required Qualifications: B.Tech or M.Tech in Computer Science or equivalent; 2-3 years of professional experience in web application development; proficiency in JavaScript, ES6, TypeScript, and modern frameworks like Vue or React; strong experience with Node.js services; experience with GenAI technologies; and experience using AI coding assistants. Desired Skills: Experience with Angular.js, AWS, UI component building, responsive design, API development, and data visualization. Proficiency in unit testing (vitest, jest) and E2E testing (Playwright, Cypress) is preferred, along with familiarity with CI/CD, Agile methodologies, MCP, AI agent frameworks, and LLM API/SDK integrations. Benefits include health, life, and disability insurance, retirement plans, flexible work accommodations, and career progression planning.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

JavaScriptES6TypeScriptVue.jsReactNode.jsGenAIAngular.jsAWSUI componentsResponsive web designAPI developmentData VisualizationvitestjestPlaywrightCypressCI/CDScrumKanbanAgileMCPAI agent frameworksLLM APIsAI SDK

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Development of Agentic AI Systems
The core mandate is to build AI tools, workflows, and agents that form the foundation of an agentic system for financial intelligence. You must demonstrate proficiency in integrating LLM APIs, AI SDKs, and understanding agentic design patterns to deliver scalable AI capabilities.
Full-Stack Web Engineering
You are expected to build and maintain high-quality web applications using Node.js for backend services and modern frameworks like Vue.js or React for the frontend. This includes building responsive UI components and robust APIs to support the AI platform.
Engineering Best Practices and Quality Assurance
The role requires strict adherence to software development standards, including code reviews, documentation, and version control. You must be proficient in unit testing (vitest, jest) and E2E testing (Playwright, Cypress) to ensure the reliability of the AI-driven platform.
Cross-Functional Collaboration
As part of a geographically diverse team, you must effectively collaborate with product teams and other engineers. You will need to articulate technical decisions and work within Agile frameworks like Scrum or Kanban to support high-visibility enterprise projects.

Likely challenges to think through

Balancing Rapid Innovation with Enterprise Stability
Working in a newly formed AI Foundry team involves building from the ground up, which can lead to shifting requirements. Prepare by discussing how you manage technical debt while iterating quickly on experimental AI features in a high-visibility environment.
Complexity of Agentic Workflows
Designing agentic systems involves managing non-deterministic AI outputs and complex state management. Prepare by reviewing agentic design patterns and how to implement robust error handling and monitoring for LLM-integrated services.
Remote and Global Team Coordination
The role requires working across different geographies, which can impact communication and development velocity. Prepare by highlighting your experience with asynchronous communication, documentation, and maintaining alignment in a distributed team setting.

Practice your answers

Technical practice

Node.js Architecture for AI Agents

What to coverExplain how you would structure a Node.js service to handle asynchronous LLM API calls while maintaining system responsiveness. Discuss strategies for managing state in agentic workflows and how you ensure high availability for these services.

Frontend State Management with React or Vue

What to coverCompare the state management patterns in React versus Vue when building complex, data-heavy financial dashboards. Explain how you ensure UI components remain performant and responsive when handling real-time data updates.

Testing Strategies for AI-Driven Applications

What to coverDescribe your approach to testing non-deterministic AI outputs. Discuss how you integrate unit testing frameworks like Vitest or Jest with E2E tools like Playwright to validate both the UI and the underlying agent logic.

Integrating LLM APIs and SDKs

What to coverDiscuss the trade-offs between using high-level AI SDKs versus direct REST API integrations with LLMs. Address how you handle error rates, rate limiting, and token management in a production environment.

TypeScript Best Practices in Large Codebases

What to coverHow do you leverage TypeScript to improve code maintainability and reduce runtime errors in a full-stack application? Provide examples of how you use interfaces or generics to manage complex data structures from financial APIs.

CI/CD Pipelines for Modern Web Apps

What to coverOutline the components of a robust CI/CD pipeline for a hybrid team. Explain how you automate testing and deployment to ensure that code changes do not break existing agentic workflows.

Responsive Design and Data Visualization

What to coverExplain your process for building responsive UI components that display complex financial data. Discuss the libraries or techniques you prefer for ensuring data visualizations remain readable across different device sizes.

Agentic Design Patterns and MCP

What to coverExplain your understanding of the Model Context Protocol (MCP) and how it facilitates communication between AI agents and external tools. Discuss how you would design a modular agent system that is scalable and easy to extend.

Behavioural practice

Collaborating in Geographically Diverse Teams

What to coverDescribe a situation where you had to coordinate with remote team members across different time zones to meet a project deadline. Focus on the communication tools and documentation practices you used to maintain alignment.

Adapting to New AI Technologies

What to coverProvide an example of a time you had to quickly learn and implement a new GenAI tool or framework. Explain how you evaluated its suitability for your project and integrated it into your existing development workflow.

Handling Technical Debt and Maintenance

What to coverTell me about a time you identified a performance bottleneck or maintainability issue in an existing application. Describe the steps you took to troubleshoot the problem and how you communicated the necessary changes to stakeholders.

Balancing Innovation with Best Practices

What to coverDescribe a scenario where you had to balance the need for rapid prototyping of an AI feature with the requirement for high-quality, maintainable code. How did you ensure the final implementation met engineering standards?

Sharpen your knowledge

Topics to prepare

Agentic Design Patterns
The role focuses on building agentic systems for financial intelligence. Review concepts such as autonomous agents, tool-use, planning, and memory management in LLM-based architectures. Exercise: Sketch a system architecture for an AI agent that retrieves real-time financial data using external APIs and processes it to answer user queries.
Modern Web Framework Architecture
The position requires proficiency in Vue.js or React. Focus on component lifecycle, state management, and reactivity models. Exercise: Compare the reactivity systems of Vue 3 and React, specifically how they handle state updates and re-rendering in complex UI components.
Node.js Service Development
The role involves building Node.js services for AI workflows. Review asynchronous programming, event loops, and building scalable RESTful or GraphQL APIs. Exercise: Design a Node.js service that integrates an LLM API, including error handling, rate limiting, and logging for production-grade reliability.

Skills to revise

LLM API and SDK Integration
Hands-on experience with LLM APIs is required. Exercise: Build a small Node.js application that uses an AI SDK (like LangChain or Vercel AI SDK) to interact with an LLM, implementing a simple prompt chain or tool-calling mechanism.
Automated Testing (Vitest/Playwright)
The role prioritizes unit and E2E testing. Exercise: Write a suite of unit tests for a frontend component using Vitest and create an E2E test script in Playwright that simulates a user interaction flow on a web form.
TypeScript Proficiency
TypeScript is essential for maintainable code. Exercise: Refactor a legacy JavaScript module into TypeScript, focusing on defining robust interfaces for API responses and complex data structures used in UI components.

Your preparation checklist

Build a GenAI-integrated web application
Develop a project using Node.js and React or Vue that integrates with an LLM API. Demonstrate your ability to manage AI SDKs and handle asynchronous data flows, which are central to the AI Foundry team's work.
Prepare a technical walkthrough of agentic design patterns
Create a brief presentation or document explaining how you have implemented or would implement agentic workflows, specifically referencing your familiarity with MCP or similar AI agent frameworks.
Demonstrate testing proficiency with modern frameworks
Prepare code samples that showcase unit testing with Vitest or Jest and E2E testing with Playwright or Cypress. Ensure these tests cover complex UI components and API service layers.
Formulate questions about the AI Foundry platform architecture
Prepare thoughtful questions regarding how the team balances scalability with the reliability required for financial intelligence tools, and how they integrate AI coding assistants into their CI/CD pipelines.
Review your experience with geographically diverse teams
Prepare specific examples of how you have successfully collaborated in an Agile (Scrum/Kanban) environment with remote or global team members, focusing on communication and documentation best practices.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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