We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Director, AI Delivery and Governance at Katch. . Location: Remote- US. About Katch. . . Katch is a leading healthcare technology company specializing in payment integrity and subrogation solutions. We partner with health plans, providers, and other stakeholders to identify, recover, and prevent payment errors—helping our clients reduce costs and improve operational efficiency. Our innovative platform combines advanced analytics, deep industry expertise, and a collaborative approach to deliver faster, more accurate recoveries and better outcomes across the healthcare ecosystem..  . . At Katch, we’re building a fast-growing team that thrives in a startup environment. We look for curious, resourceful problem-solvers who are comfortable wearing multiple hats, working with ambiguity, and moving quickly to deliver results. Ideal candidates are collaborative by nature, eager to learn, and passionate about driving innovation in healthcare. If you’re energized by solving complex challenges and want to make a measurable impact, you’ll feel right at home here..  . Job summary. . The Director, Al Delivery and Governance role is a hybrid role that bridges the gap between high-level technical architecture and team management. They are responsible for the end-to-end design, development, and deployment of scalable AI solutions that solve complex enterprise challenges. . .  . . Responsibilities. . . Technical Leadership. : Direct the design and implementation of advanced machine learning (ML) models, generative AI pipelines, and agentic workflows.. . Architectural Oversight. : Design scalable AI infrastructure, including MLOps/LLMOps pipelines, to move models from experimental phases into hardened production systems.. . Team Management. : Lead and mentor a team of AI/ML engineers, setting technical standards, conducting code reviews, and fostering professional growth.. . Strategic Alignment. : Partner with cross-functional stakeholders (Product, Data Engineering, C-suite) to align AI initiatives with business goals and roadmaps.. . Governance & Ethics. : Implement "secure-by-design" methodologies, ensuring AI solutions are ethical, transparent, and compliant with regulatory standards. . . . . AIRB Model Review. : Lead the technical validation of machine learning models within the Advanced Internal Ratings-Based (AIRB) framework, ensuring all empirical models for PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) meet strict supervisory standards.. . Rigorous Validation. : Oversee the documentation and review of "challenger models" against "champion models" to evaluate performance gains while adhering to regulatory pre-notification and approval cycles.. . Progress Tracking & Reporting. : Establish and maintain automated dashboards to track model development lifecycle progress, from initial data preparation through to final regulatory submission and approval.. . Explainability & Transparency. : Ensure all sophisticated ML techniques used in AIRB contexts remain interpretable for stakeholders and regulators, avoiding "black box" complexity that violates Capital Requirements Regulation (CRR).. . Audit & Compliance Liaison. : Serve as the primary technical point of contact for internal audit teams and external regulators, documenting any changes to rating criteria or model weights as required by Basel III and other global standards. . . . . Regulatory Knowledge. : Deep understanding of Basel II/III, CRR3, and specific EBA (European Banking Authority) or local central bank guidelines for machine learning in credit risk.. . Statistical Auditing. : Proficiency in performing grade migration analyses and monitoring historical default trends to verify that rating definitions are applied consistently.. . Model Risk Management. (MRM): Experience implementing risk-based assessment tools (like the AI Integrative Risk-Based (AIRB) model) to achieve ethical and regulatory compliance. . . . . Gatekeeping & Standards. : Define the "Go/No-Go" criteria for moving models from R&D to production. This includes setting benchmarks for accuracy, fairness, and safety.. . Model Inventory Management. : Maintain a centralized registry of all active AI models, tracking their version history, data lineage, and "last review" date.. . Bias & Ethics Auditing. : Lead regular internal audits to identify algorithmic bias or "hallucinations" in LLMs, presenting mitigation strategies to the board.. . Cross-Functional Liaison. : Translate complex technical risks into business terms for Legal, Risk, and Compliance stakeholders during board reviews.. . . Client Governance (External Transparency). . . Technical Advisory. : Act as the technical lead during client steering committee meetings, explaining how their data is used, protected, and partitioned.. . SLA & Performance Tracking. : Create transparent reporting for clients that tracks model performance against agreed-upon Service Level Agreements (SLAs).. . Trust & Transparency Documentation. : Author "Model Cards" or technical whitepapers for clients that detail model limitations, training data origins, and security protocols.. . Incident Response. : Lead the technical investigation and client communication strategy if a model behaves unexpectedly or violates a governance policy in a client environment.. . .  . . Qualifications. . Required:. . . AI/ML Expertise. : Deep knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), neural networks, and computer vision.. . Programming Mastery. : Expert proficiency in Python (often preferred), Java, or C++, along with frameworks like TensorFlow, PyTorch, and LangChain.. . Cloud & MLOps. : Significant experience with cloud platforms (AWS, Azure, GCP) and operational tools like Docker, Kubernetes, and MLflow.. . Experience. : Typically requires 8-10+ years in software engineering with a specialized track record in deploying production-grade AI systems.. . Education. : A master’s or Ph.D. in Computer Science, AI, or a related quantitative field is preferred. . . .  . . Nice to Have:. . . Hands-on experience with Palantir Foundry or Azure AI Foundry or Databricks platforms.. . Experience in forward-deployed or consulting roles.. . .  . . Our ideal candidate:. . . Stays curious, asking questions before making assumptions.. . Collaborates thoughtfully and problem solves.. . Takes ownership, stepping forward when direction is unclear.. . Stays future-ready by learning, adapting, and applying new tools.. . Acts with integrity, doing the right thing even when no one is watching.. . Safeguards trust, protecting people, clients, and data as necessary.. . Speaks up, flagging risks early and owning solutions.. . . We offer a comprehensive compensation and benefits package that is rewarded based upon a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.. The base salary range for this role in all geographic locations in the US is $200,000-$250,000. . Benefits. . . Comprehensive medical, dental, and vision coverage. . Wellness program with resources for healthy living. . Health Savings Account (HSA) and Flexible Spending Account (FSA) for tax-free savings . . Tuition reimbursement opportunities. . Generous PTO so you can recharge. . Paid holidays and sick time. . Leave options to support life’s biggest moments. . Life and Disability insurance through Unum. . Voluntary coverage options for added peace of mind (Critical Illness, Accident, Hospital Indemnity, Legal, and Identity Protection). . Employee Assistance Program (EAP) for free, confidential counseling and support. . Backup care when you need it for children, elders, and pets through Care.com. . Remote work options available for many roles. . Flexible schedules in select positions. . . For more information about Katch, visit KatchIQ.com.. .  . .  . . Equal Employment Opportunity at Katch. . Katch is an equal opportunity employer and is committed to providing equal employment opportunity to all applicants and employees. We do not discriminate on the basis of race, color, ancestry, religion, sex (including pregnancy), national origin, age, disability (physical or mental), genetic information, sexual orientation, gender identity or expression, marital status, citizenship, military or veteran status, or any other characteristic protected by applicable federal, state, or local law.. . Katch participates in E‑Verify as required by applicable law.. . In accordance with applicable state and local laws, Katch does not inquire about an applicant’s salary history during the recruitment process.. . If you require a reasonable accommodation to complete any part of the application or recruitment process, please contact our recruiting team.. . For information on how we collect and use personal data, please review our Privacy Notice at . www.KatchIQ.com