Salesforce Developer Principal AI Engineer

External Auditing Financial Services Industry Standards Technical Authority Multi-Agent Systems Regulatory Compliance Regulatory Frameworks Architectural Patterns Artificial Intelligence Regulatory Requirements Enterprise Architecture Software Design Patterns Authorization (Computing) Ethical Standards And Conduct, The Principal AI Architect, Responsible AI is the enterprise’s chief technical authority on responsible AI design and governance-by-architecture. This individual defines the standards, reference architectures, and technical guardrails that ensure every AI/ML system, from classical ML to agentic AI, meets regulatory, ethical, and quality thresholds before reaching production. The role bridges deep technical fluency with enterprise strategy, translating board-level risk appetite into enforceable architectural patterns across the full AI lifecycle., * Define and maintain enterprise Responsible AI standards, policies, and technical guidelines covering fairness, explainability, robustness, privacy, and safety across all AI/ML modalities (predictive, generative, agentic).

• Establish model risk tiering frameworks aligned with regulatory requirements (e.g., EU AI Act risk categories, NIST AI RMF, FDA/SaMD where applicable) and map technical controls to each tier.
• Lead Enterprise Architecture Review Board (EARB) reviews for AI/ML solutions, ensuring compliance with responsible AI standards before production deployment.
• Partner with Legal, Compliance, Privacy, and InfoSec to translate regulatory and contractual obligations into testable technical requirements.
• Develop and evangelize an enterprise AI ethics review process including impact assessments, red-teaming protocols, and human-in-the-loop escalation criteria for high-risk use cases.
• Mentor and coach ML Engineers, Data Scientists, and Platform Engineers on responsible AI patterns and anti-patterns; create reusable design patterns, templates, and decision frameworks.
• Represent the enterprise’s responsible AI posture to external auditors, regulators, customers, and industry working groups.
• Track the evolving responsible AI landscape (tooling, regulation, academic research) and recommend adoption of emerging capabilities., Irving, TXOn-Site Tooling Research AI Safety Leadership Governance Statistics Ethical AI Agentic AI Testability Red Teaming Communication Risk Appetite Responsible AI Pharmaceuticals Computer Science Machine Learning Applied Research External Auditing Financial Services Industry Standards Technical Authority Multi-Agent Systems Regulatory Compliance Regulatory Frameworks Architectural Patterns Artificial Intelligence Regulatory Requirements Enterprise Architecture Software Design Patterns Authorization (Computing) Ethical Standards And Conduct +0 Ai Data Scientist Sr. PNC Pittsburgh, PA | Birmingham, AL | Cleveland, OH | Dallas, TXHybrid Planning Management Automation Governance Algorithms Data Mining Coordinating Data Science Risk Management Solution Design Data Processing Customer Service Business Process Machine Learning Unstructured Data Business Decisions Business Objectives Process Optimization Advanced Mathematics Workplace Inclusivity Artificial Intelligence Data-Driven Decision Making Swift (Programming Language) Enterprise Risk Management (ERM) Generative Artificial Intelligence +0

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Salesforce Developer Principal AI Engineer CBRE Richardson, TX*On-Site Sales CI/CD CrewAI LangChain Operations Leadership Consulting Management Innovation Communication Observability Mortgage Loans Responsible AI Microsoft Azure Trustworthiness Knowledge Graph Machine Learning Containerization Platform Mindset Edge Intelligence Project Management Influencing Skills Program Management Workflow Management Amazon Web Services Facility Management Resource Allocation Predictive Modeling Property Management Software Engineering Lifecycle Management Investment Management Commercial Real Estate Artificial Intelligence Real Estate Investments Concept Drift Detection Software Design Patterns Python (Programming Language) Generative Artificial Intelligence MLOps (Machine Learning Operations) Artificial Intelligence Infrastructure +0

AI Safety Leadership Governance Statistics Ethical AI Agentic AI Testability Red Teaming Communication Risk Appetite Responsible AI Pharmaceuticals Computer Science Machine Learning, * Degree or equivalent and typically requires 13+ years, with 8+ years, of direct work related experience. Less years required if has relevant Master’s or Doctorate qualifications., * Extensive experience in AI/ML engineering, architecture, or applied research with at least 3 years focused on AI governance, fairness, or safety.

• Deep expertise in at least two: bias/fairness measurement, explainability methods (SHAP, LIME, counterfactual), adversarial robustness, differential privacy, or AI safety alignment.
• Demonstrated experience authoring enterprise-level AI standards, policies, or reference architectures adopted across multiple business units.
• Strong working knowledge of regulatory frameworks: NIST AI RMF, EU AI Act, ISO 42001, SOC 2 AI considerations, and sector-specific requirements (healthcare, financial services).
• Experience presenting technical governance topics to executive leadership and board-level audiences.

Preferred Experience/Skills:

• Experience with agentic AI architectures and the unique governance challenges they present (tool-use authorization, multi-agent orchestration, autonomous decision boundaries).
• Contributions to responsible AI open-source projects, publications, or industry standards bodies.
• Healthcare or pharmaceutical industry experience.
• Master’s degree (in Computer Science, AI/ML, Statistics, or related quantitative field) or PhD preferred.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson’s pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$225,200 - $375,400

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:

McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.

McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: careers.mckesson.com.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.