Senior AI Systems Engineer

Responsibilities

• Build governed ingestion pipelines and CDC/ELT integrations from SaaS systems and cloud billing sources into Snowflake.
• Develop conformed data models, tested transformations, semantic layers, freshness monitoring, lineage, drift alerting, and reliable backfills.
• Implement Snowflake RBAC, row- and column-level policies, masking, Okta-based identity inheritance, and cost attribution.
• Build retrieval layers with chunking, embedding pipelines, index freshness, and retrieval-quality evaluation.
• Create governed AI Landing Zones across AWS, GCP, Azure, and Snowflake, along with templates, deployment paths, documentation, and office hours for internal agent builders.
• Operate the core IT platform and automate employee joiner, mover, and leaver workflows through HRIS systems.
• Own cloud account structures, SCPs, IAM, and network segmentation while partnering with Security.
• Deliver production agents, data products, SaaS integrations, and automations that eliminate recurring manual work.

Requirements

• 7+ years of experience at the intersection of data engineering and infrastructure.
• Deep experience with Snowflake as an analytical warehouse, operational intelligence layer, and governed platform.
• Strong data modeling and transformation experience with dbt or an equivalent, plus orchestration using Dagster, Airflow, or Prefect.
• Strong software engineering fundamentals with required Python and assumed SQL; Go or Bash is a plus.
• Experience designing infrastructure as code at scale with Pulumi, CDK, or CloudFormation.
• Hands-on production experience with AI and LLM agents, RAG, tool-calling, and MCP or equivalent technologies.
• Deep AWS experience, including Bedrock, IAM, EventBridge, and Lambda, plus working knowledge of GCP and Azure.
• Experience integrating SaaS systems through REST, webhooks, and event hooks.
• Experience with Okta SSO and Workflows, Jamf packaging, Google Workspace, Jira, and HRIS-based employee lifecycle automation.
• Nice-to-have experience includes Kafka, Kinesis, Snowpipe, data observability and lineage tools, retrieval-quality evaluation, SOC 2 or ISO 27001, and production agents or automations that retired recurring work.
• Strong root-cause orientation, bias for shipping, and exceptional communication and people skills.

Benefits

• Hybrid work from the Boston office with some flexibility outside East Coast hours for global employees and customers.
• Collaborative, fast-moving environment with direct impact, ownership, creativity, curiosity, and opportunities to work with cutting-edge technology.