Posted Oct 16, 2026

(Entry Level) _GenAI Associate Engineer_ W2 only

Apply Now
Role : Generative AI Engineer (GenAI Engineer) Location :USA PST time zone (Remote / Hybrid ). Time zone to follow: PST Number of roles – 4 Job description : • 2–3 years of software development experience, including candidates with strong academic, internship, personal, or open-source project experience. • Strong programming fundamentals in Python, JavaScript/TypeScript, Node.js, or Golang. • Basic hands-on experience with React, Next.js, REST APIs, Git, and GitHub. • Hands-on familiarity with AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT, Windsurf, or Replit AI. • Fundamental understanding of Generative AI, LLMs, Prompt Engineering, AI Agents, and RAG. • Basic understanding of MCP (Model Context Protocol) and how AI agents can interact with tools, APIs, and external systems. • Exposure to building AI/LLM-based applications, chatbots, workflows, or proof-of-concepts through academic, internship, personal, or open-source projects. • Understanding of APIs, JSON, web services, and basic application architecture. • Familiarity with Git-based development and software engineering practices. • Strong analytical and problem-solving skills with the ability to learn new technologies quickly. • Strong curiosity and enthusiasm for experimenting with emerging AI tools, frameworks, and developer productivity technologies. Preferred / Good-to-Have Skills: • Exposure to LangChain, LangGraph, CrewAI, AutoGen, or similar AI/agent frameworks. • Familiarity with vector databases, embeddings, semantic search, and RAG implementations. • Basic exposure to Docker, Kubernetes, AWS, Azure, or Google Cloud Platform. • Experience integrating AI applications with enterprise systems, databases, or third-party APIs. • Experience with MCP servers, tool calling, function calling, or agentic workflows. • Personal projects, GitHub contributions, hackathons, or academic projects involving GenAI, LLMs, or AI agents. • Ability to use AI coding tools to rapidly convert ideas into functional prototypes or demos. • Strong product mindset and ability to understand a problem and translate it into a working technical solution. • Comfortable working in a fast-paced environment involving rapid experimentation, ambiguity, and continuous learning. • Ability to balance rapid development with code quality, security, maintainability, and engineering best practices.