What are the responsibilities and job description for the AI Fullstack Developer/Architect - W2 - ONLY LOCAL TO CALIFORNIA position at Jobs via Dice?
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Geopaq Logic, is seeking the following. Apply via Dice today!
Job Title: AI Fullstack Developer/Architect
Location: San Jose, CA
Duration: 1 Year of Contract
Required Qualifications & Skills
Experience: Proven experience(5~8 yrs. for Middle Level & 9 yrs. for Sr. Level) as a Full Stack Developer with specialized experience in AI model deployment.
Backend Skills: Strong proficiency in Python and frameworks like FastAPI or Django.
Frontend Skills: Experience with modern JavaScript frameworks (React.js Node.js,Next.js, Plotly Dash FastAPI).
AI/ML Knowledge: Familiarity with AI model integration (e.g., OpenAI API, LangChain, PyTorch).
Cloud/DevOps: Experience in Cloud platforms (AWS, Google Cloud Platform, Azure) and container technologies (Docker, Kubernetes).
Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
Preferred Qualifications
Experience with generative AI and agentic architectures.
Understanding of data privacy and security in AI applications.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field
Job Title: AI Fullstack Developer/Architect
Location: San Jose, CA
Duration: 1 Year of Contract
Required Qualifications & Skills
Experience: Proven experience(5~8 yrs. for Middle Level & 9 yrs. for Sr. Level) as a Full Stack Developer with specialized experience in AI model deployment.
Backend Skills: Strong proficiency in Python and frameworks like FastAPI or Django.
Frontend Skills: Experience with modern JavaScript frameworks (React.js Node.js,Next.js, Plotly Dash FastAPI).
AI/ML Knowledge: Familiarity with AI model integration (e.g., OpenAI API, LangChain, PyTorch).
Cloud/DevOps: Experience in Cloud platforms (AWS, Google Cloud Platform, Azure) and container technologies (Docker, Kubernetes).
Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
Preferred Qualifications
Experience with generative AI and agentic architectures.
Understanding of data privacy and security in AI applications.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field