Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Hybrid/remote flexibility, popular AI title, metro location, and broad GenAI/full-stack requirements increase competition.
GenAI and full-stack engineering skills are broadly transferable across industries, enabling cross-industry mobility.
Explicit 0–2 year requirement plus practical GenAI and full-stack skill expectations create moderately strict technical filters.
Design, develop, and maintain full-stack and GenAI-enabled applications using Python, FastAPI, React, LLMs, prompt engineering, and RAG pipelines.
Build and enhance AI assistants, chatbots, workflow automation tools, and intelligent dashboards to improve engineering and business workflows.
Collaborate with cross-functional teams to convert business requirements into software features, including specification-driven development and deployment using Docker and cloud basics.
Bachelor’s degree in Computer Science, IT, Data Science, AI, Engineering, or related technical field.
0–2 years of professional or internship experience in software development with hands-on Python, REST APIs, and GenAI concepts.
Proficiency in Python programming and backend frameworks (FastAPI, Flask, Django); familiarity with JavaScript/TypeScript and React.
Experience or practical understanding of large language models, prompt engineering, RAG, embeddings, AI APIs, and AI-assisted development tools (e.g., GitHub Copilot).
Experienced with full-stack or backend development involving GenAI technologies and AI-assisted coding tools in professional or project settings.
Comfortable working in agile teams applying SDLC practices including code reviews, testing, and documentation.
Familiar with secure engineering, responsible AI practices, Docker, CI/CD pipelines, and cloud deployment basics.