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Tier-1 brand, mid-level AI role in metro, and broad full-stack requirements increase applicant competition.
Requires specific GenAI, agentic AI, and cloud-native experience, limiting easy cross-industry transferability.
Multiple explicit years and mandatory GenAI, cloud, and full-stack tech requirements enforce strict filters.
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Lead and deliver full-stack AI-enhanced products from concept through production to achieve customer and business outcomes with cost-efficiency.
Own architecture integrity, technical stack alignment with enterprise standards, code quality, and maintenance, including managing dependencies and cloud costs.
Mentor and lead engineering teams, collaborate cross-functionally to rapidly create lean, scalable, and supportable AI/ML solutions including GenAI and agentic capabilities.
Bachelor's degree in computer science, software engineering, data science, machine learning, or related field.
6+ years full-stack software engineering experience with Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, plus testing frameworks.
3+ years building AI/ML and agentic applications including GenAI with LLM integration (OpenAI, Anthropic, or open-source), RAG pipelines, prompt engineering, vector DBs, and AI agent orchestration.
3+ years cloud-native engineering experience on Azure, AWS, or GCP with AI/ML services and cost-aware (FinOps) responsibilities; 1+ year leading and mentoring engineering standards adoption.
Experienced lead engineer with deep expertise in applied AI solution delivery integrating GenAI and agentic capabilities into products.
Operationally focused, accountable for balancing quality, cost, and outcome alignment across enterprise-scale, cloud-native full-stack products.
Able to translate business needs into technical designs and lead cross-functional teams through fast, experiment-driven development cycles maintaining high product and code quality.