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.
Define technical direction for AI applications, making pragmatic build-versus-buy choices and aligning roadmaps to measurable business outcomes.
Partner with data scientists, product managers, and domain experts to frame problems, test hypotheses, and iterate quickly from prototype to production.
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 operationalization
Generative AI integration
Scalable cloud-based systems
CI/CD and DevOps practices
Python, JavaScript, or Node.js proficiency
Nice-to-have
Enterprise-level integrations
Data visualization tools
Ambitious thinking and collaboration
Curiosity and perseverance
Key Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Proven Full Stack Developer experience with AI/ML focus
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 (OpenAI, bedrock, cognitive services)
Cloud platform experience (AWS, Azure, GCP)
Database knowledge (SQL, NoSQL, Snowflake)
DevOps and CI/CD experience
Microservices and containerization (Docker, Kubernetes)