Generative AI Engineer

Role : Generative AI Engineer
Remote
Contract




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 GCP.
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.