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Strong employer brand, generalist mid-level fullstack title, metro location, and broad skills increase competition.
Full-stack engineering skills are fairly transferable across industries despite AI platform specifics.
Moderate tech breadth required across frontend, backend, APIs, databases, and AI integration.
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Design, develop, and maintain full stack product features including front end interfaces and backend services on an agentic AI platform.
Collaborate across product, AI/ML, data engineering, and DevOps teams to build production-ready, reliable, and secure product experiences.
Build responsive, enterprise-grade user interfaces and backend APIs, integrating AI/ML services, data pipelines, and databases in a cloud-native environment.
Strong experience with at least one modern front end framework (React, Angular, Vue, Next.js, or equivalent).
Hands-on experience building backend services/APIs using Node.js, Python, Java, .NET, or equivalent modern backend stacks.
Working knowledge of REST APIs, GraphQL, microservices, API security, error handling, and service integration.
Experience with relational or NoSQL databases such as PostgreSQL, MySQL, MongoDB, Redis, or equivalents.
Engineer capable of ownership across the full stack: frontend, backend, APIs, and database integration.
Experience working in early-stage, fast-moving environments balancing speed, engineering quality, security, and maintainability.
Comfortable integrating AI/ML services and data pipelines into product workflows and user experiences.