Angular Jobs in Web3

We are looking for a Junior Software Engineer who is comfortable working across the full product development stack, including frontend, backend, and AI-powered features.

In this role, you will build internal tools, automation platforms, data-driven products, and AI-enabled workflows. You will work on user-facing interfaces, backend services, APIs, data integrations, and LLM-powered capabilities. We are looking for someone who can move fast, learn quickly, and use AI tools effectively to deliver end-to-end product features.

This is not a pure frontend or pure backend role. We value engineers who can take ownership of a feature from requirement understanding to UI implementation, backend logic, AI integration, testing, and iteration.

• Build and maintain end-to-end product features across frontend, backend, and AI/LLM components.

• Develop user interfaces for internal tools, dashboards, AI assistants, automation workflows, and productivity platforms.

• Build backend services, APIs, data pipelines, task workflows, and integrations with internal or external systems.

• Integrate LLM/AI capabilities into real product scenarios, such as intelligent assistants, RAG workflows, AI agents, automation tools, classification, summarization, and issue analysis.

• Use AI coding tools to improve development speed, code quality, testing, and debugging.

• Work with product, operations, support, engineering, security, and infrastructure teams to understand user needs and deliver practical solutions.

• Participate in product iteration based on user feedback, usage data, and business impact.

• Write clean, maintainable code and contribute to documentation, testing, and engineering best practices.

• Bachelor’s degree or above in Computer Science, Software Engineering, Engineering, or a related field.

• Solid programming foundation and ability to learn new technologies quickly.

• Hands-on experience with at least one frontend framework, such as React, Vue, Angular, or similar.

• Hands-on experience with at least one backend language or framework, such as Python, Go, Java, Node.js, FastAPI, Spring Boot, Express, or similar.

• Basic understanding of frontend engineering, including component design, state management, API integration, UI debugging, and browser fundamentals.

• Basic understanding of backend engineering, including API design, databases, authentication, async jobs, logging, monitoring, and service reliability.

• Real experience with LLM/AI applications, such as: LLM API integration/ Prompt engineering/ RAG/AI agents/ Tool/function calling/ Workflow automation/ Text classification / summarization / extraction/ LLM output evaluation

• Comfortable using AI coding tools such as Cursor, Claude Code, GitHub Copilot, Cline, OpenCode, or similar tools in daily development.

• Strong ownership, good communication skills, and willingness to work on ambiguous problems.

• Ability to deliver practical solutions with both engineering quality and user experience in mind.

• Experience building AI-powered products, internal tools, dashboards, workflow automation systems, or data-driven applications.

• Experience with LLM/Agent/RAG frameworks such as LangChain, LlamaIndex, Dify, AutoGen, CrewAI, OpenAI API, Anthropic API, Hugging Face, or similar.

• Experience with vector databases, embeddings, semantic search, knowledge bases, or retrieval systems.

• Experience with observability, monitoring, alerting, incident analysis, DevOps, SRE, or workflow automation.

• Experience with UI/UX design thinking or building usable internal tools from scratch.

• Experience using AI tools to build full-stack features faster, including frontend generation, backend scaffolding, tests, and documentation.

• Personal AI projects, hackathon projects, open-source contributions, or production AI application experience.

• Good technical writing and knowledge sharing habits.

• Are comfortable working end to end across frontend, backend, and AI features.

• Are AI-native and actively use AI tools to improve their own productivity.

• Have built real AI/LLM applications, not just used ChatGPT.

• Care about user experience and practical business value.

• Can quickly turn ambiguous requirements into working product features.

• Are curious, hands-on, and fast-learning.

• Think about reliability, maintainability, security, and AI output quality.

• Communicate clearly and collaborate well with cross-functional partners.

• Build a dashboard or internal tool that helps users understand operational data and AI-generated insights.

• Develop a user interface for an AI assistant or agent workflow.

• Build backend APIs and data pipelines for AI-powered automation.

• Integrate LLMs into product workflows for classification, summarization, recommendation, or issue analysis.

• Build a RAG-based knowledge assistant for domain-specific Q&A.

• Develop an agent workflow that can call tools, retrieve data, and complete multi-step tasks.

• Use AI coding tools to accelerate frontend, backend, testing, and documentation work.

• Improve product experience based on user feedback and usage data.