Lead AI Ops Engineer, Application

What you'll do

• Own the technical design and architecture for high-ambiguity or high-consequence AIOps builds.
• Write and ship production code for the hardest components of the data-to-automation pipeline.
• Establish technical standards and reusable patterns for feature engineering, model evaluation, and remediation scaffolding.
• Lead the progression of use cases toward self-healing automation and provide evidence for production approval.
• 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 leadership.
• 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 software or data engineering experience, including sustained ownership of production systems at meaningful scale.
• Track record of being a technical authority, leading design reviews, and setting engineering standards for senior-level engineers.
• Deep expertise productionizing ML models using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Advanced fluency with LLM-based techniques, including setting guardrails and evaluation criteria.
• Demonstrated experience designing and defending production automation for a regulated institution’s production systems.
• Demonstrated judgment under real incident pressure, including the experience to halt automation mid-incident.
• US military experience gained through military service or as a military spouse / domestic partner.