• Design, build and operate the cloud infrastructure that Chronograph runs on • Maintain a first-class developer experience by building reliable internal tooling. For example, you’ll contribute to our PR environment platform, which allows developers to quickly spin up an entire application stack with its own production-scale, ZFS-based database clone • Build and use AI-assisted tooling to automate operational work, with sound judgment on safety and cost • Monitor application performance and help developers debug production issues • Improve the performance, scalability, and security of our infrastructure • Participate in an on-call rotation, respond to production incidents with infrastructure assistance, and help teams pursue observability improvements during the post-mortem process

• Be the technical owner of Curative’s F&A platform. • Pull, transform, and reconcile large volumes of financial data. • Collaborate closely with F&A team to identify discrepancies and develop solutions. • Build AI agents to automate support and billing questions. • Manage codebase, architectural decisions, and quality control of a Python + TypeScript application. • Handle sensitive PHI and financial information with data privacy discipline. • Monitor platform performance and propose changes based on operational metrics. • Maintain stakeholder relationships and co-own the product plan with F&A.

• Design, build, and operate orchestration frameworks supporting long-running, stateful AI workflows and agent execution systems • Develop distributed retrieval architectures spanning vector, graph, search, and relational data platforms • Build shared platform services, reusable runtime components, and tool registries supporting AI capabilities across Fortress products • Implement resilient event-driven and change-data-capture (CDC) pipelines with strong consistency, retry, and fault-tolerance guarantees • Develop typed APIs and integration contracts supporting AI workflows and platform interoperability • Improve scalability, performance, reliability, and operational efficiency across orchestration and retrieval infrastructure • Support secure multi-tenant deployments across cloud, hybrid-cloud, and air-gapped environments • Build and maintain observability, telemetry, tracing, centralized logging, governance, and policy enforcement tooling • Contribute to engineering standards and architectural patterns for orchestration, retrieval, and platform infrastructure • Collaborate cross-functionally with platform engineering, product engineering, security, and AI teams to support platform adoption and operational excellence • Participate in troubleshooting, incident response, root cause analysis, and operational support activities related to platform infrastructure • Continuously evaluate emerging technologies, tooling, and engineering practices relevant to AI infrastructure and distributed systems

• Develop and implement data architectures that align with business needs and leverage Snowflake’s capabilities for data warehousing, data lakes, and data engineering. • Design and implement data solutions that address specific business needs, such as BI, ETL, and AI/ML. • Assist with migration of data from legacy systems to Snowflake. • Ensure data accessibility, security, and compliance with relevant regulations and industry standards. • Design and implement data pipelines for ingesting, transforming, and loading data into Snowflake from various sources. • Design and implement data models within Snowflake, considering data relationships, data types, and storage requirements. • Monitor and optimize query performance, data ingestion, and transformation processes within the Snowflake environment. • Collaborate with stakeholders, including business users, data engineers, data scientists, and other IT teams, to understand requirements and deliver solutions. • Evaluate and select appropriate tools and technologies for data integration, transformation, and analytics within the Snowflake ecosystem. • Provide technical leadership and guidance to data engineering and data analytics teams.