Fullstack Software Engineer
New
D
DiagridAI infrastructure
Remote India, Core US overlap window of 8:30 PM to 12:00 AM IST.Full-Time
Salary not disclosed
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Job Details
- Required Skills
- Node.jsPostgreSQLMySQLTypeScriptReactRESTful APIsDistributed Systems
Requirements
- Have strong professional experience developing production applications with TypeScript and Node.js.
- Have experience building modern web applications with React or a similar frontend framework.
- Understand backend architecture, REST APIs, asynchronous programming, and service integrations.
- Have experience with databases such as PostgreSQL, MySQL, or similar technologies.
- Be familiar with cloud-native development, containerization, and modern deployment practices.
- Understand software engineering fundamentals, including testing, performance, security, and maintainability.
- Be able to independently own technical projects and deliver high-quality solutions.
- Be comfortable solving problems in an environment where requirements evolve.
- Be available for the core US overlap window of 8:30 PM to 12:00 AM IST.
- AI-powered applications, AI agents, LLM integrations, AI frameworks, or agent development patterns are nice to have.
- Distributed systems, event-driven architectures, microservices, Dapr, Kubernetes, Docker, cloud infrastructure, real-time systems, messaging, or asynchronous workflows are nice to have.
- Open-source contributions, developer-focused products, or experience at an early-stage or high-growth technology startup are nice to have.
Responsibilities
- Design, develop, and maintain fullstack applications using TypeScript, Node.js, and modern frontend frameworks.
- Build APIs, integrations, and backend services for AI infrastructure and developer-facing products.
- Develop tools and services that help developers build, deploy, manage, and operate AI agents in production.
- Own features through technical design, implementation, testing, deployment, and ongoing improvement.
- Create interfaces, APIs, and workflows that make distributed systems easier to use.
- Collaborate with AI, platform, product, and engineering teams to solve technical challenges.
- Write maintainable, well-tested code and contribute to architectural decisions and engineering practices.
- Address distributed systems, asynchronous workflows, integrations, and reliability challenges in production AI applications.
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