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Fullstack entry-level role with generalist title but niche AI/RAG skills, moderate applicant density.
AI-focused fullstack skills transfer across tech sectors but less to non-AI industries.
Explicit 6–12 month requirement plus mandatory AI, React, backend and LangChain-related skills.
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Support development and integration of RAG pipelines and LLM-powered AI features across frontend (React) and backend (Node.js/Python).
Assist in deployment, testing, and maintenance of AI workloads and APIs on AWS cloud infrastructure.
Collaborate with senior engineers and cross-functional teams to deliver production-grade GenAI applications while ramping up skills quickly.
6 months to 1 year experience in AI/NLP fundamentals and full-stack development.
Proficiency in Python with understanding of NLP basics (tokenization, POS tagging, NER) and text vectorization methods (BoW, TF-IDF, Word2Vec/embeddings).
Familiarity with React, JavaScript/TypeScript, Node.js, Git, and basic SQL/NoSQL CRUD operations.
Conceptual understanding of transformer architectures, LLMs (e.g., GPT/LLaMA), RAG concepts, vector databases (FAISS or ChromaDB), and AWS services like Lambda and DynamoDB.
Early-career engineer with foundational knowledge in AI/NLP and full-stack development looking to grow into production AI application development.
Comfortable working under guidance within a team, collaborating closely with senior engineers and cross-functional roles.
Capable of learning fast, following code quality practices, and communicating progress and blockers clearly.