Senior Infrastructure Engineer - Hybrid

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

We are seeking a Senior Staff Infrastructure Engineer with deep Oracle and Exadata expertise, a strong engineering mindset, and hands‑on experience with infrastructure as code, cloud automation, and AWS. This role will modernize resilient database platforms, establish reusable engineering standards, reduce manual work, and help the broader team scale.

The ideal candidate treats infrastructure as software through automation, version control, testing, peer review, and clear documentation. As a senior technical leader, this person will solve complex challenges, mentor engineers, and apply AI as a responsible productivity accelerator while retaining ownership of technical decisions and production outcomes.

This role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).

• Design, build, and operate secure, highly available Oracle database platforms across Exadata and Oracle RDS.
• Engineer resiliency using Oracle RAC, Data Guard, Share Plex, backup and recovery capabilities, and Exadata platform features.
• Lead capacity planning, performance and cost optimization, migrations, upgrades, consolidations, and cloud transitions.
• Ensure platforms meet enterprise expectations for security, availability, recoverability, performance, and service levels.

• Design reusable infrastructure automation using Terraform, Open Tofu, Ansible, AWS Cloud Formation, Python, and APIs.
• Apply software engineering practices to infrastructure, including modular design, version control, testing, validation, peer review, and continuous integration and delivery.
• Establish practical standards, guardrails, playbooks, and documentation that allow teams to provision and change infrastructure consistently and safely.
• Reduce operational complexity and manual work through automation and standardization.

• Lead troubleshooting and root‑cause analysis for complex production issues while improving observability, alerting, reliability, and operational maturity.
• Partner across application, cloud, security, architecture, and infrastructure teams to deliver enterprise‑critical outcomes.
• Lead cross‑functional technical work streams, influence engineering direction, and translate complex challenges into sustainable solutions.
• Mentor engineers and strengthen infrastructure‑as‑code, automation, cloud, and software engineering capabilities across the team.

• The successful candidate will use AI as a responsible productivity accelerator while retaining ownership of technical decisions and production outcomes.
• Use AI‑assisted tools to accelerate coding, automation, analysis, troubleshooting, testing, refactoring, and documentation.
• Critically evaluate AI‑generated output and validate it through domain expertise, system knowledge, and production feedback.
• Apply AI within enterprise security, privacy, governance, compliance, logging, and audit requirements.
• Apply practical knowledge of generative AI, prompt engineering, retrieval‑augmented generation, agentic workflows, model evaluation, and AI observability to infrastructure engineering challenges.
• Explore practical use cases such as log and metric analysis, incident investigation, configuration review, and…