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Mid-senior generalist fullstack title, metro locations, and broad skillset requirements increase applicant competition.
Core fullstack skills are transferable but enterprise GenAI and cloud experience increases domain specificity.
Explicit 6+ years requirement plus many mandatory tech and cloud/AI skills enforces strict filtering.
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Own end-to-end implementation of critical full-stack features across web applications, APIs, integrations, cloud-native services, and AI-powered capabilities.
Ensure delivery of scalable, secure, reliable, and high-performance enterprise-grade digital products with strong engineering standards including code quality, testing, and DevOps.
Collaborate closely with architects, TPMs, product managers, DevOps, and peer developers to translate architecture and AI use cases into production-ready solutions while mentoring junior engineers.
6+ years experience building enterprise-grade full-stack applications with strong ownership from design through delivery.
Proficiency in React, JavaScript/TypeScript, HTML5, CSS3, and Python backend frameworks like FastAPI, Django, or Flask.
Experience with relational/NoSQL databases, REST APIs, cloud platforms (Azure, AWS, or GCP), containerization tools (Docker, Kubernetes), and CI/CD/DevOps pipelines.
Hands-on with AI integration including LLM APIs, prompt design, retrieval-augmented generation (RAG), AI monitoring/guardrails, and secure software development lifecycle.
Technically strong in full-stack development with a focus on scalable, maintainable, AI-enabled enterprise applications in cloud environments.
Experienced in translating high-level architecture and AI solution intents into detailed, production-ready implementations.
Capable of troubleshooting production issues independently while driving engineering best practices, mentoring, and continuous improvement within cross-functional teams.