Staff Applied AI Engineer
Core
Build data pipelines, predictive/prescriptive models, and token-efficient LLM-powered agents/workflows to solve business problems like churn forecasting and optimization.
Role type
Staff Applied AI Engineer (GenAI/ML)
Builds
Production ML models, GenAI agents, data pipelines, and enterprise reference architectures.
Domain
Enterprise analytics, Generative AI, Data Engineering
Required skills
Snowflake data engineering, SQL, data modeling, applied statistics (confidence intervals), predictive/prescriptive analytics, LLM/agentic systems (LangGraph, CrewAI), RAG (chunking, hybrid search, reranking), Python, software engineering (testing, CI/CD), architecture design.
Preferred skills
Inference optimization (quantization, vLLM, TensorRT), MLOps/LLMOps, platform building, AI strategy.
Technologies
Snowflake, LangGraph, Claude Agent SDK, CrewAI, vLLM, TensorRT, Python, AWS, Google Cloud, Azure.
Responsibilities
Build pipelines combining Snowflake and unstructured data; Produce churn and retention analytics with confidence intervals; Develop predictive and prescriptive models; Design and deploy token-efficient LLM-powered agents; Define enterprise reference architectures and governance standards; Establish monitoring and guardrails for drift, bias, and safety.
Seniority
Staff, hands-on IC with strategic scope
