Lead AI Ops Engineer, Infrastructure

What you'll do

• Own the technical design and architecture for high-ambiguity and high-consequence AIOps builds.
• Ship production code and infrastructure-as-code for the hardest components of the data-to-automation pipeline.
• Establish reusable patterns for telemetry-consuming feature pipelines, topology-graph designs, and remediation scaffolding.
• Determine which infrastructure use cases are ready for self-healing automation and provide the justifying evidence.
• Serve as the primary technical escalation point during major incidents and make real-time "kill switch" decisions.
• Mentor senior engineers on technical depth and judgment to grow the next generation of technical leads.
• Lead postmortems to convert incident lessons into updated engineering standards.
• Represent engineering in engagements with Model Risk Management and Internal Audit to resolve complex control considerations.

What we're looking for

• Bachelor's degree; OR 4 years of relevant education and/or experience.
• 7+ years of hands-on infrastructure, platform, or site-reliability engineering experience with sustained ownership of production systems at scale.
• Proven track record as a technical authority leading design reviews and setting engineering standards for senior-level engineers.
• Deep expertise productionizing ML models for infrastructure operational data using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Advanced hands-on expertise with infrastructure-as-code and orchestration tooling including Terraform, Ansible, and Kubernetes operators.
• Demonstrated experience designing and defending production automation for a regulated institution's infrastructure.
• Demonstrated judgment under real incident pressure to make critical calls during production incidents.
• US military experience gained through military service or as a military spouse/domestic partner (preferred).