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Metro locations, popular fullstack title, mid-level requirement, and broad full-stack/AI skillset increase competition.
Core full-stack skills are transferable but GenAI and enterprise analytics experience create moderate domain specificity.
Explicit 6+ years plus mandatory React, Django, cloud, containerization, and GenAI experience makes filters strict.
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Own end-to-end design, development, and delivery of enterprise-grade full-stack features using React and Django across web, APIs, cloud, and AI-enabled application layers.
Translate architectural designs into scalable, secure, maintainable production systems collaborating with architects, TPMs, and cross-functional teams.
Drive engineering standards including code quality, testing, DevOps, AI feature integration, troubleshooting, and mentoring junior engineers.
6+ years of hands-on full-stack software engineering experience with ownership from design to delivery.
Strong expertise in React or similar (Angular, Vue) with JavaScript/TypeScript, and backend proficiency in Python frameworks like Django, FastAPI, or Flask.
Experience with cloud platforms (Azure, AWS, or GCP), containerization (Docker, Kubernetes), relational/NoSQL databases, and automated testing tools.
Hands-on integration of AI features using LLM APIs, prompt orchestration, retrieval-augmented generation (RAG), with knowledge of GenAI failure modes and secure/quality guardrails.
Experienced in delivering complex technical solutions with practical system design and performance optimization for enterprise-scale applications.
Strong technical ownership with ability to act as a dependable technical point of contact for implementation issues and cross-functional collaboration.
Demonstrated skills in integrating AI/GenAI capabilities into production systems and contributing to engineering best practices, automation, and mentorship.