Jobs at Doma

Provides Tier 1 IT support through ticketing, email, chat, and phone; troubleshoots hardware, software, connectivity, Microsoft 365, VPN, and access issues. Supports employee onboarding and offboarding, account and MFA requests, asset tracking, documentation, escalation, and knowledge-base development. The role also includes cybersecurity cross-training, security incident awareness, ITSM process adherence, and evaluating AI-enabled support automations.

Provides Tier 1 IT support for hardware, software, Microsoft 365, connectivity, VPN, access, and endpoint issues. Supports employee onboarding and offboarding, identity and access requests, asset tracking, documentation, ticket management, and escalation of complex or security-sensitive incidents. The role also includes cybersecurity cross-training, knowledge-base development, AI-enabled workflow automation, and service improvement activities.

Own and evolve Looker as the company-wide business intelligence platform. Build dashboards, data models, pipelines, and integrations connecting Snowflake and other sources. Ensure data quality and provenance, support operational reporting, and partner with Finance, Data Science, and business teams. Help develop AI- and LLM-based agentic reporting tools that enable self-service analytics. Communicate technical concepts across the organization and provide insights for operational decision-making.

Owns Azure cloud infrastructure, Kubernetes, DevOps, infrastructure-as-code, CI/CD, GitOps, secrets management, databases, data warehouses, observability, and reliability. Leads AI-assisted infrastructure engineering standards and practices, manages and mentors engineers and engineering managers, contributes hands-on to architecture, coding, incident response, and platform improvements, and partners with Security and Corporate IT.

Build, deploy, and maintain production-grade ML systems across the full model lifecycle. Translate business goals into ML solutions, monitor model performance and drift, perform analyses and experiments, and collaborate with data engineers, product, and domain experts to improve risk assessment and underwriting outcomes.