The posting
Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the “12 Angry Seniors.” Their mission continues to guide everything we do.
Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.
Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.
At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.
The Job:
As an AI Engineering Manager, you’re the hands-on leader for our organization’s architecture, delivery, and team development. Your team builds enterprise AI solutions that improve how the organization operates, makes decisions, and serves its members.
This role is accountable for demonstrating and setting technical direction, leveling up engineering practices and the engineers. You will represent our team by partnering across business, data, security, and technology functions. You will ensure AI products are thoughtfully designed, responsibly governed, securely delivered, operationally reliable, and aligned to enterprise priorities.
Essential Job Functions:
Hands-on Technical Contribution
- Lead by example, contributing to our core products and participating in development activities
- Develop prototypes and showcase new capabilities available on our cloud platforms as they become available
- Expand our AI platform by owning functional expansions (sample areas include Agent Orchestration, Knowledge, Skills, and Data Integrations)
Architecture Leadership & Technical Direction
- Define and steward enterprise-grade AI platform/solution architectures, ensuring systems are scalable, secure, maintainable, and aligned to emerging technology frameworks.
- Set technical standards, design principles, and decision frameworks for AI applications, data integrations, agentic workflows, and production platforms.
- Guide architectural tradeoff decisions across speed, quality, risk, cost, reusability, and long-term operability.
Engineering Discipline & Delivery Management
- Establish disciplined engineering practices for requirements definition, estimation, solution design, code quality, testing, documentation, release management, and production readiness.
- Lead teams through SCAN’s SAFe Agile delivery rhythms, ensuring technical work is prioritized, sequenced, communicated, and completed with appropriate rigor.
- Drive continuous improvement in engineering processes, delivery predictability, observability, supportability, and operational excellence.
People Leadership & Engineer Development
- Coach, mentor, and develop engineers; set clear expectations, provide actionable feedback, grow technical judgment, and increase ownership over time.
- Build team capability in AI engineering, cloud software development, architecture, security, responsible AI, and enterprise delivery practices.
- Create a high-accountability team culture that values curiosity, clarity, craftsmanship, collaboration, and responsible innovation.
Enterprise Partnership & Leader-to-Leader Engagement
- Engage senior leaders to translate enterprise priorities into executable AI product and platform roadmaps.
- Represent engineering perspectives in cross-functional planning, governance, risk discussions, and prioritization forums.
- Influence stakeholders through clear communication, sound judgment, practical tradeoff analysis, and shared accountability for business outcomes.
Responsible AI, Security, Governance & Operational Accountability
- Ensure AI systems are designed and delivered with responsible AI practices, including transparency, traceability, explainability, fairness, privacy, security, and human oversight.
- Partner with security, compliance, legal, governance, and platform teams to embed appropriate controls into architecture and delivery processes.
- Own engineering accountability for solution documentation, risk awareness, production readiness, operational support, and continuous improvement.
Your Qualifications:
- Bachelor's Degree or equivalent experience in Computer science, Engineering, or a related field required
- Master’s Degree in Computer science, Engineering, or a related field preferred
- Advanced ability to define, evaluate, and govern AI solution architectures, including LLM-based systems, RAG, vector embeddings, agent orchestration, data integration, and platform patterns.
- Ability to lead engineering teams through disciplined delivery practices, including design reviews, coding standards, testing strategy, documentation, CI/CD, observability, release readiness, and support models.
- Proficiency with Azure AI Services, Azure AI Foundry, enterprise cloud data platforms (Databricks and Snowflake), and integration with platforms such as Microsoft 365.
- Strong technical fluency in Python or equivalent languages, REST APIs, ML/LLMOps tooling, and modern application frameworks sufficient to guide architectural decisions and coach engineers.
- Ability to coach engineers, build technical judgment, delegate effectively, provide actionable feedback, and grow ownership and accountability within the team.
- Leader-to-leader communication skills, with ability to engage executives, peer leaders, and cross-functional partners in prioritization, tradeoff, governance, and adoption conversations.
- Strong business partnering skills, self-direction, and influence; able to define roadmaps, persuade skeptics, and drive adoption of new processes or technologies.
- Demonstrates curiosity, initiative, and continuous learning while creating the systems, practices, and coaching that help the broader engineering team adapt to new frameworks and technologies.
- Leadership - Develops others, sets clear expectations, and builds accountable engineering teams
- Business Insight - Connects technology strategy to enterprise priorities, operational needs, and member impact
- Decision Quality - Makes sound architectural and delivery tradeoffs under ambiguity
- Strategic Mindset - Creates durable engineering strategies, standards, and roadmaps that scale beyond a single project
- Collaborates - Engages effectively with peer leaders and cross-functional partners to drive shared outcomes
- Software Development – Writes code and contributes to team projects for AI capabilities deployed in cloud environments.
Preferred Certifications or Licenses:
- Microsoft Certified: Azure AI Engineer Associate
- Relevant certifications in cloud platforms, AI engineering, machine learning, data engineering, or software development are beneficial.
- Additional certifications in Responsible AI, Data Governance, or Cybersecurity are advantageous.
Experience Preferred:
- Extensive experience (8+ years) in software engineering, AI engineering, data engineering, machine learning, automation, or enterprise technology delivery, ideally within regulated industries such as healthcare.
- Demonstrated experience leading or managing engineers, including coaching, performance feedback, workload planning, technical mentorship, and team capability development.
- Proven ability to define and govern solution architecture for enterprise-scale AI or digital transformation initiatives, including cross-functional collaboration with business, healthcare, data, security, compliance, and technology teams.
- Experience establishing engineering practices for production-grade applications, APIs, data pipelines, automation workflows, cloud-based AI services, testing, documentation, release management, and operational support.
- Familiarity with Azure AI Foundry, Azure OpenAI, Azure AI Services, Databricks, Snowflake, or similar enterprise AI and data platforms is highly valued.
- Strong leader-to-leader communication and stakeholder management skills, with ability to translate enterprise priorities into technical direction, align peers, and drive adoption across diverse teams.
What's in it for you?
- Base Salary Range: $125,400 to $215,975 annually
- An annual employee bonus program
- Robust Wellness Program
- Generous paid-time-off (PTO)
- 11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
- Excellent 401(k) Retirement Saving Plan with employer match
- Robust employee recognition program
- Tuition reimbursement
- An opportunity to become part of a team that makes a difference to our members and our community every day!
We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now!
At SCAN we believe that it is our business to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects our community through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more.
SCAN is proud to be an Equal Employment Opportunity and Affirmative Action workplace. Individuals seeking employment will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender perception or identity, age, marital status, disability, protected veteran status or any other status protected by law. A background check is required.
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Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)
