Vice President, Platform Engineering
Department: Information Technology
Employment Type: Full Time
Location: US-California-San Jose
Compensation: $297,300 - $408,800 / year
Description
The Vice President, Platform Engineering is a member of the Technology leadership team and is accountable for the technology platforms that power Align’s digital products and operations: Data, AI, Cloud, API, and Identity. This leader sets the strategy, architecture, and operating model for these platforms and treats them as products that let engineering and business teams build faster, more securely, and at scale.
The VP translates business needs into a coherent platform architecture and serves as the primary technical and business authority on Align's platform capabilities. Responsibilities span engineering, securing, and optimizing cloud infrastructure; building a trusted, well-governed data foundation; delivering shared AI and machine learning capabilities with responsible AI guardrails; and providing secure identity and API services for workforce, customer, and partner ecosystems. The role ensures all platforms meet regulatory and compliance requirements, including SOX, PCI DSS, and applicable privacy regulations.
This leader builds and scales high-performing engineering teams and partners closely with R&D, product, security, and business stakeholders. Strong technical depth, influential leadership, and the ability to drive change in a complex, fast-moving enterprise environment are essential.
The role reports to the Chief Digital Officer and is located in San Jose, CA, or Raleigh, NC.
Role expectations
Platform Strategy and Leadership
- Define and own the multi-year vision, strategy, and roadmap for Align’s enterprise platforms (Data, AI, Cloud, API, and Identity), making sure they directly enable the company’s digital product and business strategy.
- Build, lead, and scale high-performing platform engineering organizations. Attract and develop top talent, and foster a culture of engineering excellence, ownership, and continuous improvement.
- Operate the platforms as products, with clear internal customers, service levels, adoption metrics, and feedback loops, so product and engineering teams can build faster and more reliably.
- Partner with the Chief Digital Officer, business unit leaders, R&D, product, security, and infrastructure teams to translate business needs into platform capabilities and build consensus on architecture and investment priorities.
- Own platform budgets, vendor strategy, and build-versus-buy decisions. Lead technology evaluations, RFI/RFP processes, proofs of concept, and vendor negotiations.
- Establish architecture standards, reference patterns, and governance that drive modular, reusable, and well-abstracted solutions across the product and enterprise portfolio.
Data Platform
- Lead the architecture, engineering, and operation of the enterprise data platform, including data lake/lakehouse, warehousing, streaming, and integration capabilities.
- Deliver scalable, reliable data pipelines and event-driven data flows that give analytics, AI, and operational systems trusted, timely data.
- Implement data governance, quality, lineage, cataloging, and master data practices that make data discoverable, accurate, and compliant.
- Ensure appropriate protection of sensitive and regulated data, including patient and customer data, in line with privacy regulations (e.g., HIPAA, GDPR).
AI Platform
- Define and execute the enterprise AI platform strategy, providing shared infrastructure, tooling, and services that let teams build, deploy, and scale AI and machine learning solutions safely and efficiently.
- Lead integration with foundation model providers and AI platforms (e.g., OpenAI, Anthropic, AWS), including model access, orchestration, retrieval, agent frameworks, and evaluation capabilities.
- Establish MLOps and LLMOps practices for model training, deployment, monitoring, versioning, and cost management.
- Implement responsible AI guardrails, including security, privacy, bias, and safety controls, in partnership with legal, compliance, and security.
- Continuously evaluate emerging AI technologies and drive adoption of those that deliver measurable business value.
Cloud Platform
- Own the architecture, engineering, security, and optimization of Align’s cloud and hybrid infrastructure, with AWS as the primary cloud environment.
- Deliver self-service infrastructure, container orchestration (Docker, Kubernetes), and internal developer platform capabilities that improve release velocity, developer productivity, and system stability.
- Drive the adoption of DevSecOps, CI/CD, infrastructure-as-code, and observability best practices across cloud and on-premises environments.
- Lead re-platforming and modernization of legacy systems to cloud-native architectures.
- Manage cloud cost, performance, resilience, and disaster recovery through FinOps practices and SRE disciplines.
- Partner with R&D to manage and integrate engineering tools (e.g., Jira, Confluence, GitHub), driving efficient adoption across the engineering organization.
Identity and API Platform
- Lead the Identity and Access Management strategy for workforce, customer, and partner identities, including SSO, MFA, privileged access, and lifecycle management, using standards such as OAuth, OIDC, and SAML.
- Advance zero-trust security principles across applications, endpoints, and infrastructure.
- Build and scale the enterprise API platform, including API gateway, management, developer portal, and lifecycle governance, so internal teams and external partners can integrate securely and consistently.
- Drive API-first and event-driven integration patterns (e.g., Kafka) that decouple systems and accelerate the delivery of new digital products.
- Define API design standards, versioning, security, and monitoring practices across the enterprise.
Security, Compliance, and Operational Excellence
- Ensure all platforms meet regulatory and compliance requirements, including SOX and PCI DSS, and maintain audit readiness.
- Embed secure-by-design principles and secure code practices throughout platform engineering.
- Define and report on platform KPIs, including availability, performance, adoption, developer experience, and cost efficiency.
- Maintain current documentation of platform architecture, integrations, and dependencies across the enterprise portfolio.
Additional responsibilities:
- Other duties may be assigned
What we're looking for
Leadership and Experience
- 10 or more years of professional experience in large-scale, distributed technology environments, including at least 8–10 years in enterprise or platform architecture.
- Proven senior leadership experience building and managing multi-disciplinary platform organizations spanning data, AI, cloud, and/or identity and API engineering.
- Demonstrated success operating internal platforms as products, with measurable improvements in developer productivity, reliability, adoption, and cost efficiency.
- Proven track record re-platforming large legacy systems to modern, cloud-native architectures.
- Experience managing significant budgets, vendor relationships, and technology selection processes, including RFI/RFP, proofs of concept, and quantitative and qualitative evaluation.
Data Platform
- Deep experience with modern data architectures, including data lakes/lakehouses, warehousing, streaming, and data integration.
- Strong understanding of data governance, quality, lineage, cataloging, and the protection of sensitive and regulated data.
AI Platform
- Strong technical background in AI and machine learning, with hands-on experience building or integrating AI platforms, models, and AI-driven services or agents.
- Familiarity with foundation model providers (e.g., OpenAI, Anthropic, AWS), MLOps/LLMOps practices, and model evaluation and monitoring.
- Commitment to responsible and ethical AI, including safety, privacy, and governance controls.
Cloud Platform
- Extensive experience with AWS or an equivalent cloud provider, including architecture, security, cost optimization, and resilience.
- Hands-on experience with microservices and containerized applications (Docker, Kubernetes), distributed caching, and load balancing.
- Experience implementing DevSecOps, CI/CD, infrastructure-as-code, observability, and SRE practices at scale.
Identity and API Platform
- Strong expertise in Identity and Access Management, including SSO, MFA, privileged access, and zero-trust architectures, with authentication standards such as OAuth, OIDC, and SAML.
- Deep understanding of API ecosystems, API management and governance, and partner integration dynamics.
- Validated experience with SOA, design patterns, web services standards (HTTP, REST, JSON, XML, SOAP), and event-driven architecture using Kafka or similar technologies.
Security and Compliance