AI Engineer

Champion an AI-first mindset, embedding AI into data workflows, internal tools, and business processes

Design and maintain AI-native data solutions and scalable data/AI pipelines for analytics, RAG, fine-tuning, and copilots

Build and operate agentic workflows (e.g., Crew AI, LangGraph, AutoGen) for complex multi-step business processes

Develop and run LLM-integrated pipelines using Claude, Glean, Gemini, Snowflake Cortex and enterprise copilots

Define prompt engineering patterns, evaluation methods, and guardrails for production AI applications

Translate business problems into data + AI solutions that deliver clear, actionable business insights

Design robust data architectures spanning batch, streaming, and AI inference layers

Build Snowflake-based pipelines using Python, dbt, and Airflow for analytics and AI workloads

Implement and maintain data ingestion and reverse-ETL using Fivetran and Hightouch

Model data for MDM, Marketing, Finance, and Customer Success (adoption, retention, telemetry)

Manage AWS infrastructure (S3, EC2, IAM, Lambda, Step Functions, Glue) for data and AI platforms

Enforce data privacy, governance, and compliance, including PII controls in Snowflake and AWS

Implement data and AI observability with tools like Monte Carlo and Datadog

Optimize SQL models and Python transformations to support feature stores and data products

Apply CI/CD, Git, testing, and code review practices to data and AI engineering

Partner with stakeholders across functions to gather requirements and design end-to-end data + AI architectures

Own and monitor solutions to meet SLAs, SLOs, data freshness, and business KPIs

Maintain clear documentation for data platforms, AI systems, and architecture

Troubleshoot and resolve data and AI issues, driving root-cause fixes

• Deliver work using Agile/Scrum, acting as a strong team player and mentor