GenAI Full Stack Engineer

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Requirements:

• 5+ years of Full Stack AI Engineering experience.
• 5+ years experience with Next.JS., React.
• 5+ years experience building microservices.
• 2+ years writing Python.
• Familiarity with cloud platforms (AWS, GCP, Azure) for AI deployment.
• Experience with Vector databases, Tailwind or Bootstrap CSS, Langchain, Open AI.
• Strong database management and data modeling skills.
• Solid experience with Git, GitHub/GitLab, and Agile development practices.
• Experience with AI-driven systems (e.g., chatbots, recommendation engines, NLP).

Responsibilities:

• Design, develop, and maintain full-stack web applications with a focus on AI-driven features.
• Use Tailwind or Bootstrap CSS to build websites.
• Build responsive, user-centric front ends using modern JavaScript frameworks, with a strong emphasis on Next.js and React in Typescript.
• Develop and optimize robust back-end services and APIs using Node.js, Python (Flask/Django), and Express.js.
• Apply software engineering best practices including code quality, testing, performance optimization, and scalability.
• Integrate GenAI models (e.g., LLMs, RAG, agentic systems) and APIs into web applications for automation, personalization, and analytics.
• Work with AI/ML frameworks such as Langchain, OpenAI, Amazon Bedrock, Google Vertex AI, and others.
• Develop intelligent, task-oriented systems using agentic architecture.
• Implement cloud-native AI services for scalable and secure deployment.
• Deploy AI and web solutions in cloud environments (AWS, Azure, GCP) with strong attention to scalability and security.
• Build and maintain microservices, RESTful APIs, and GraphQL interfaces.
• Use containerization tools (Docker, Kubernetes) and CI/CD pipelines to ensure smooth development and deployment workflows.
• Leverage MLOps tools and best practices for model lifecycle management and monitoring.
• Design and manage databases (SQL, NoSQL, Firebase, MongoDB), ensuring seamless data flow between applications and AI models.
• Build data pipelines and backend systems to support real-time AI inference and analytics.

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