Lead full-stack delivery of AI-enabled products from architecture to production, applying modern engineering practices to unlock data, automate decisions, and create seamless user experiences
Job Summary
Lead full-stack delivery of AI-enabled products from architecture to production, applying modern engineering practices to unlock data, automate decisions, and create seamless user experiences.
Partner with data scientists, product managers, and domain experts to frame problems, test hypotheses, and iterate quickly from prototype to production.
You will work with advanced platforms, real-world data, and ambitious collaborators to deliver AI capabilities that tangibly speed research, sharpen decision-making, and expand access for patients.
Matching Summary
Lead full-stack delivery of AI-enabled products from architecture to production, applying modern engineering practices to unlock data, automate decisions, and create seamless user experiences.
Skills & Requirements
Must-have
Full-stack AI application delivery
Machine learning pipelines
Generative AI integration
Scalable AI systems design
DevOps practices and CI/CD
Cloud platforms (AWS, Azure, GCP)
Nice-to-have
Enterprise-level integrations
Data engineering projects
Data visualization tools
Key Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Proven Full Stack Developer experience with AI/ML focus
Proficiency in Python, JavaScript, or Node.js
Experience with frontend frameworks (React, Angular, Vue.js)
Experience with backend technologies (RESTful APIs, Django, Flask)
Expertise in ML frameworks (PyTorch, Scikit-learn)
Experience with Generative AI models and techniques
Experience with cloud platforms (AWS, Azure, GCP)
Strong understanding of databases (SQL, NoSQL, Snowflake)
Experience with DevOps practices and CI/CD
Knowledge of microservices and containerization (Docker, Kubernetes)