Full Stack - AI Product Engineer (US/VN)

Rapidly design & launch AI Solutions and prototypes: Rapidly iterate and prototype internal AI deployments for a company to drive up to $30M in value, including customer service tools, internal analytics, and AI-driven workflows. 

• Enterprise Integration: Develop and maintain scalable backend services and APIs for AI-powered applications, while implementing usable and performant frontend interfaces. Ensure high performance, reliability, and seamless AI model integration, working closely with data scientists to deploy and optimize models in production.
• AI Model Implementation: Some understanding of fine-tuning LLMs for various enterprise applications, leveraging retrieval-augmented generation (RAG) and data pipelines. 
• Product Development & Rapid Iteration: Quickly prototype and test AI solutions, refining them based on user feedback and business needs. 
• Best Practices & Innovation: Stay up-to-date with the latest AI/ML products and advancements to continuously explore internal AI products that might be relevant to the business. 
• Implement A/B testing and analytics to measure AI-driven user experience improvements, observability and usage.

• 5+ years of experience in full stack software engineering, with a strong focus on product development. 
• Strong proficiency in backend development using Node.js (with TypeScript), Python (FastAPI, Django), or Go, with experience in building scalable APIs (RESTful, GraphQL, gRPC).
• Experience with database design and management using PostgreSQL, MySQL, or NoSQL databases (MongoDB, DynamoDB, Redis).
• Ability to use JavaScript/TypeScript and modern frontend frameworks (React, Vue.js, Next.js, etc.) to build highly usable and performant user interfaces.
• Ability to quickly prototype, test, and iterate solutions and products
• Experience in asynchronous processing, message queues (Kafka, RabbitMQ, or SQS), and microservices architecture.
• Experience with performance optimization and security best practices in backend systems and frontend usability.
• Experience with containerization and cloud deployment (Docker, Kubernetes, Helm) on AWS, GCP, or Azure.
• Experience working with AI-driven applications and integrating ML models via APIs or pipelines.
• Strong understanding of data pipelines, and ETL workflows
• Strong problem-solving skills, AI-first thinking and the ability to understand complex business challenges and translate them into AI-driven solutions - experience using AI for coding.
• Good communication skills, in English, with the ability to collaborate across technical and non-technical teams.