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Strong employer brand, metro location, mid-level 5+yrs, and broad AI/full-stack requirements increase applicant competition.
High due to specialized AI-native production, LLMs, agents, and vector retrieval skills limiting transferability.
Explicit 5+ years, mandatory AI/ML production experience, and full-stack plus cloud requirements tighten shortlisting.
Design, build, and operate end-to-end full-stack AI-powered applications and platforms including frontend, backend services, APIs, data layers, and cloud infrastructure.
Develop and integrate AI/ML capabilities such as LLMs, RAG, embeddings, semantic search, and agentic workflows into production-grade solutions.
Own software delivery lifecycle from concept, prototype to production operation with focus on scalability, reliability, security, and AI-native development practices.
5+ years of software engineering experience building and operating production-quality software systems.
Hands-on experience with full-stack development including frontend (React, TypeScript/JavaScript) and backend services, APIs, microservices, distributed systems.
Experience in AI/ML production applications involving LLMs, embeddings, vector search, agentic workflows, integrating AI model platforms such as OpenAI, Anthropic, or Google.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience.
Strong full-stack engineering expertise combined with practical knowledge in modern AI technologies and production-grade deployment capabilities.
Experience designing and deploying scalable, cloud-native distributed systems with AI integration focusing on AI-native development and engineering productivity improvements.
Demonstrated ownership in technical decisions, mentoring engineers, and elevating engineering standards for AI-powered software in secure, reliable environments.