Principal Data & AI Platform Engineer, DataOps

Role overview Architect and build platform capabilities that make large-scale data operations more reliable, observable, and resilient. The focus is on operating and supporting data systems, using AI and agentic approaches to detect failures, assess data quality, and guide or automate responses. The role combines hands-on engineering with technical direction, cross-team architecture work, and mentoring.

Responsibilities - Design and implement AI-enabled features for operating data platforms, including failure detection, recovery, and escalation. - Build monitoring that identifies data anomalies, assesses their impact, and recommends or triggers appropriate actions. - Put AI capabilities into production with evaluation, observability, human review, and fallback processes. - Lead architecture and design reviews and establish reusable patterns for resilient data operations. - Partner with engineering, platform, cloud, security, and data consumer teams to define requirements and deliver solutions. - Contribute directly to implementation, troubleshooting, and performance and scalability improvements; mentor engineers on complex problems.

Requirements - Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience. - At least 10 years across data, software, or platform engineering, including senior architecture and large-scale system design. - At least 3 years applying AI, generative AI, or agentic capabilities to engineering, platform, or operational workflows. - Experience building large-scale data processing systems used by a broad group of users or downstream consumers. - Hands-on experience operating AI-augmented solutions, including evaluation, monitoring, failure handling, and support. - Strong knowledge of modern data platforms such as Databricks or Snowflake and distributed data processing; ability to lead technical work across teams.

Nice to have - Familiarity with agentic AI frameworks, semantic or context layers, and methods for evaluating models. - Experience in data quality, observability, lineage, fault tolerance, or automated remediation at scale. - Experience in healthcare or another regulated industry.

Benefits and work setup - Travel is expected to be up to 10%, subject to business needs. - The stated base salary range is $200,000–$230,000. The listing also describes paid leave and an inclusive benefits program, but detailed benefit terms are not provided in the source.