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Niche LLM/MLOps skillset but metro mid-level role yields moderate competition.
Requires specialized LLM/MLOps and vector DB experience, limiting cross-industry transferability.
Explicit 5+ years and mandatory LLM, full-stack, MLOps, and cloud skills make filtering strict.
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Design and implement scalable front-end and back-end architectures for AI-driven products using React/Vue/Angular and Python/Node.js.
Lead integration and optimization of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems focusing on latency, reliability, and cost efficiency.
Collaborate with Data Scientists and MLOps engineers to deploy, monitor, and improve AI systems in production, including API development and CI/CD pipeline management.
Minimum 5 years of experience as Full Stack Software Engineer with at least 1 year in AI/ML integration.
Strong skills in front-end development with TypeScript/JavaScript and frameworks like React or Next.js.
Advanced back-end development in Python (preferred) or Node.js with experience building scalable APIs.
Proficiency with LLM APIs (OpenAI, Gemini, Claude), LangChain or LlamaIndex frameworks, containerization (Docker), and cloud deployment (AWS or GCP).
Experienced full stack engineer bridging data science and product engineering in AI applications.
Deep expertise in integrating and optimizing LLMs and building Retrieval-Augmented Generation systems.
Skilled in end-to-end AI product development including API design, MLOps, and deployment on cloud platforms.