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Mid-level metro fullstack role with broad AI-cloud requirements at a well-known analytics firm increases competition.
Core fullstack skills are transferable, but enterprise GenAI and cloud requirements raise domain specificity.
Explicit 6+ years and mandatory full-stack, cloud, containerization, and AI integration skills make shortlisting highly strict.
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Own design and implementation of critical full-stack features across web applications, APIs, cloud-native services, and AI-powered capabilities.
Ensure high code quality, performance, security, and operational excellence while collaborating with architects, TPMs, and cross-functional teams to deliver scalable and production-ready systems.
Integrate AI capabilities such as LLM APIs, prompt orchestration, and retrieval-augmented generation to build reliable enterprise AI solutions with monitoring and guardrails.
6+ years of hands-on experience building enterprise-grade full-stack applications with ownership from design through delivery.
Strong expertise in React and JavaScript/TypeScript; strong backend experience with Node.js or Python frameworks (FastAPI, Django, Flask).
Experience with cloud platforms (Azure, AWS, or GCP), containerization tools (Docker, Kubernetes), and DevOps practices including CI/CD pipelines and secure SDLC.
Hands-on experience integrating AI capabilities into applications, including knowledge of LLM APIs, prompt design, RAG, and AI feature evaluation and monitoring.
Engineer with deep practical ownership of complex full-stack projects spanning frontend, backend, cloud, and AI integration, comfortable translating architecture into robust implementations.
Experienced in building and operating AI-enabled enterprise applications with emphasis on reliability, security, and cost/performance optimization.
Effective collaborator in cross-functional and client-facing environments, with demonstrated capability to mentor juniors and uphold engineering standards.