Support global demand generation by administering Salesforce and Pardot, maintaining contact data integrity, cleansing and segmenting contact databases, supporting outbound marketing campaigns, analyzing campaign performance, and leading projects to automate workflows and produce reports that demonstrate business impact.

Design and build cloud-native microservices, REST APIs, and highly available backend services supporting large-scale data requests. Translate business requirements into scalable platform solutions, contribute to architecture modernization, and uphold engineering practices including testing, observability, CI/CD, and code reviews. Troubleshoot production issues, improve reliability, and evaluate emerging data engineering and generative AI technologies. Mentor colleagues and collaborate across technical and business teams.

Build and operate applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, MCP tools, APIs, and governed content-serving layers. The role emphasizes production reliability, provenance, security, cost and latency management, regression detection, and human-reviewed AI outputs. Responsibilities include cloud deployment, structured content modeling, telemetry, governance, mentoring, and collaboration on AI standards. Strong Python, TypeScript, AWS, API, data pipeline, and production LLM experience are required.