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Mid-level fullstack title and metro location increase competition, but niche generative-AI skills narrow applicant pool.
Highly specialized generative-AI and agentic engineering skills limit cross-industry portability.
Explicit 4–6 years plus mandatory LLM frameworks, agentic engineering, and fullstack stack make filters highly stringent.
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Design, build, and deploy AI-powered full stack applications using Python (backend) and React (frontend) combining generative AI capabilities with product engineering.
Develop and maintain agentic frameworks and LLM pipelines integrating generative AI APIs and vector databases for Retrieval-Augmented Generation systems.
Monitor, debug, optimize AI model performance in production and collaborate cross-functionally to ship end-to-end AI features.
4 to 6 years of relevant experience in AI generative full stack development.
Proficiency in Python 3.x and React.js with experience in backend frameworks like FastAPI, Django, or Flask.
Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar) and agentic system development including prompt engineering and multi-step reasoning.
Experience with RESTful/GraphQL API development, vector databases (e.g., Pinecone, Weaviate), and cloud deployment on AWS, GCP, or Azure.
Experienced in designing complex multi-step agentic loops with robust error handling and observability.
Skilled in prompt engineering, evaluation pipelines, and cost/latency optimizations for production AI systems.
Strong software engineering fundamentals with asynchronous Python, testing discipline, and capacity to work at the intersection of AI research and scalable product delivery.