Ande.ai
About
Ande is an AI-native, full-stack TypeScript platform built on React, Node.js, GraphQL, and Postgres, running on AWS and powering web, mobile, internal operations, deep integrations, and agentic workflows.
Our product sits at the intersection of enterprise workflows, hospitality operations, payments, compliance, procurement, and AI — giving engineers the opportunity to solve problems that combine polished user experiences with complex real-world systems.
Engineering at Ande is deeply product-oriented and systems-heavy. We care about:
- Type safety and shared abstractions
- Fast iteration and observable production systems
- High-quality user experiences
- Building durable foundations for a category-defining platform
PMs and engineers work closely with the business domain, contributing directly to:
- Booking experiences
- Client entertainment policies
- Venue operations
- Spend visibility and approvals
- Payments and procurement workflows
- Enterprise integrations
- AI-driven workflows that reduce manual coordination across enterprises and hospitality partners
Founders
- Lohit Sarma
- Ashish Bidadi
- Michael McDermott
Tech stack
NodeJS (Node.js)
React.jsCandid answers by the company
Remote (US shift)
Company social profiles
Jobs at Ande.ai
NodeJS (Node.js)React.jsWe are seeking a high-caliber Senior Full-Stack Engineer to lead the design, development, and deployment of our next-generation intelligent applications. In this role, you will bridge the gap between robust full-stack architecture and smart artificial intelligence integrations. You will be responsible for building scalable Node.js microservices, crafting intuitive React interfaces, and embedding AI capabilities (such as LLM APIs, autonomous agents, and smart workflows) to solve complex user problems.
As a senior member of the team, you will champion technical excellence, mentor junior developers, and influence our product roadmap.
Key Responsibilities:
AI Integration & Engineering
- Architect and implement backend systems that interface with Large Language Models (LLMs) and other AI services via APIs (e.g., OpenAI, Anthropic, or custom internal model endpoints).
- Build middleware to handle prompt engineering, context orchestration, and structural parsing of AI responses into application logic.
- Implement guardrails, caching layers, rate-limiting, and evaluation metrics for AI model outputs to ensure reliability, security, and cost-efficiency.
- Stay up-to-date with emerging generative AI patterns, model capabilities, and integration techniques to drive product innovation.
Full-Stack Development
- Backend: Build, scale, and maintain highly performant, secure, and production-ready RESTful APIs and GraphQL services using Node.js (TypeScript / Express).
- Frontend: Develop responsive, state-managed, and visually seamless user interfaces using React.js and modern state management libraries (e.g., Redux Toolkit, Zustand, React Query).
- Optimize application performance across the stack—from database query optimization to frontend rendering bottlenecks.
Architecture & Leadership
- Lead architectural decisions, promoting modular design, code reusability, and scalable system infrastructure.
- Enforce high engineering standards through rigorous code reviews, automated testing (unit, integration, E2E), and comprehensive documentation.
- Mentor and coach junior and mid-level engineers, fostering a culture of continuous learning and technical growth.
- Work closely with Product Managers, UX Designers, and stakeholders to translate ambitious product visions into concrete technical execution.
Technical Skills & Qualifications
Required Experience
- Experience: 5+ years of professional software development experience, with a proven track record of shipping production-grade SaaS applications.
- Node.js Ecosystem: Deep expertise in backend development using Node.js and TypeScript, including asynchronous programming, event-driven architecture, and microservices.
- React Ecosystem: Advanced proficiency in React, hooks, state management, and modern build tools (Vite, Webpack).
- AI Practice: 1–2+ years of practical experience integrating LLM APIs and cognitive workflows into customer-facing applications.
- Databases: Strong proficiency with relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB).
- Cloud & DevOps: Familiarity with cloud platforms (AWS, GCP, or Azure), Docker, and CI/CD pipelines.
Soft Skills
- Exceptional problem-solving skills and a proactive "ownership" mindset.
- Strong communication skills, with the ability to explain complex technical or AI concepts to non-technical stakeholders.
- Proven ability to thrive in a fast-paced, iterative environment.
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