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Mid-level seniority, common fullstack title but niche AI/LLM requirement reduces candidate pool.
Requires combined AI/LLM and full-stack enterprise experience, limiting cross-industry transfer.
Explicit 6+ years plus mandatory AI/LLM, backend, AWS, and enterprise-scale experience.
Own end-to-end delivery of AI-powered enterprise-grade full-stack applications including AI/LLM integration, backend services, cloud infrastructure, and UI components.
Integrate large language models and AI tools into production workflows such as retrieval-augmented generation pipelines and agent orchestration.
Deploy and manage AWS infrastructure components (Lambda, ECS/EKS, API Gateway, S3, RDS) and collaborate closely with PMs and stakeholders in an agile environment.
6+ years of full-stack engineering experience.
Proficiency in at least one backend language such as Python, Node.js, Java, or Go.
Hands-on production experience integrating AI/ML models or LLM APIs (e.g., OpenAI, Bedrock, LangChain).
Strong AWS deployment experience with ownership of cloud infrastructure components.
Experienced full-stack engineer comfortable leading UI delivery using modern frameworks, preferably React, with ability to build polished interfaces.
Familiar with enterprise-scale concerns including multi-tenant systems, security, observability, and CI/CD.
Skilled in client-facing collaborative agile environments, capable of managing ambiguity and communicating effectively with stakeholders.