Full Stack Developer – AI
J
JobgetherGenerative AI software
Based in India; with the opportunity to work remotely across IndiaContract
Salary15 - 20 USD per hour
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Job Details
- Required Skills
- AWSDockerNode.jsKubernetesMicrosoft AzureAngularReactPrompt Engineering
Requirements
- Bring strong experience in full-stack software development across frontend and backend application engineering.
- Have practical experience with React, Angular, and Node.js.
- Have hands-on experience with LLMs, RAG pipelines, and prompt engineering.
- Understand GenAI application architecture and AI model lifecycle management.
- Have experience with Microsoft Azure and/or AWS cloud environments.
- Know CI/CD pipelines, Docker, Kubernetes, and modern software deployment practices.
- Have a strong understanding of SQL and NoSQL databases.
- Be familiar with vector databases and data-ingestion frameworks.
- Have experience supporting production applications and troubleshooting complex technical issues.
- Be able to conduct root cause analysis and implement sustainable fixes.
- Understand AI-specific risks, including hallucinations, model drift, bias, and reliability challenges.
- Bring problem-solving, debugging, and performance optimization capabilities.
Responsibilities
- Develop, maintain, and enhance frontend applications, backend services, APIs, and microservices for production GenAI solutions.
- Implement and support AI-powered features using LLMs, RAG pipelines, and prompt engineering.
- Diagnose and resolve application and platform issues, conduct root cause analysis, and implement corrective actions.
- Optimize application responsiveness, scalability, reliability, and performance in production.
- Support application deployment and operations on Azure and/or AWS, including containerization and infrastructure management.
- Implement and maintain CI/CD pipelines and automated deployment workflows using Docker and Kubernetes.
- Develop and maintain database integrations and data-ingestion processes for SQL, NoSQL, and vector databases.
- Monitor and address GenAI reliability issues, including hallucinations, model drift, and bias.
- Collaborate with engineering, support, and platform teams to resolve incidents and deliver application enhancements.
- Identify ways to improve application availability, reduce recurring incidents, and strengthen production support practices.
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