Director, I&T Plasma Engineering

CSL•King of Prussia, PA

About The Position

The Director, I&T Plasma Engineering leads engineering and owns architecture governance across all CSL Plasma digital product domains. The role defines and owns engineering standards, practices, and technology platform strategy for internal development teams, managed service providers, and external vendors. It also governs AI and Generative AI in production across CSL Plasma, including AI features in donor-facing and operational products, AI-assisted software development, and the operational discipline required to run AI reliably at scale. This technical leadership role owns the technical foundation for reliable, scalable digital product delivery: quality standards, architectural patterns, cross-cutting engineering capabilities, and security and compliance posture. It is distinct from product delivery coordination and product strategy. The Director remains technically credible with engineers, contributes personally where judgment is required, and delegates other work effectively. The position reports to the Senior Director, Plasma I&T Applications & Operations. Direct reports include the Plasma Business Architect, AI/ML Product Engineer, Automation Engineer, Data Engineer, SRE/DevOps Engineer, and UX Designers. The responsibilities also specify direct leadership of a cross-domain team including a QA Lead and QA Automation Engineers. The role owns engineering standards and architecture governance across five Plasma digital product domains; cross-domain team leadership and development; technology platform and tooling strategy; technical quality oversight; AI strategy and production governance; and security and compliance engineering. It owns the target-state architecture for the Data Backbone and the shared engineering platform, including service templates, CI/CD pipelines, deployment patterns, observability, and security guardrails. It establishes engineering metrics, works formally with CSL Enterprise Architecture and CSL Cyber, and ensures appropriate regulatory, privacy, data protection, and responsible AI standards are embedded in engineering practices.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related field; a master’s degree is preferred.
10+ years of progressive software engineering experience, including at least 5 years in engineering leadership roles.
Demonstrated success building and leading cross-functional engineering teams across multiple technical domains.
Recent hands-on engineering experience within the last three years.
Track record of setting engineering standards, patterns, and paved paths adopted across multiple product teams.
Track record of shipping production AI systems, including evaluation, observability, guardrails, and cost management.
Product engineering depth across native mobile, full-stack web, Salesforce platform, and API and integration development.
Deep expertise in enterprise architecture, integration platforms such as MuleSoft, AWS, and Azure, and cloud-native technology strategy.
Demonstrated experience implementing, integrating, or leading enterprise initiatives involving AI, ML, and/or Generative AI.
Strong understanding of modern AI platforms, LLMs, RAG, AI evaluation, guardrails, lifecycle management, evaluation harnesses, tracing, red-teaming, agentic workflow patterns, and related cloud-native AI services.
Strong experience establishing engineering governance, including coding standards, architecture review processes, CI/CD pipelines, and technical quality metrics.
Proven ability to define and enforce security and compliance engineering standards in partnership with Cyber and Legal organizations.
Experience managing and developing senior technical staff, including architects, QA leads, and specialist engineers.
Excellent executive communication skills and ability to translate technical strategy into business language for senior leadership.
Experience shipping software in a regulated or consumer-scale environment; comfort working in regulated contexts and willingness to build working knowledge of 21 CFR Part 11, HIPAA, GxP, and EU Annex 11 as relevant to the role.

Nice To Haves

Master’s degree in Computer Science, Software Engineering, or a related field.
Life sciences, healthcare, or pharmaceutical industry experience, or direct experience with 21 CFR Part 11, HIPAA, GxP, or EU Annex 11.
Knowledge of MuleSoft Anypoint Platform, Informatica IDMC, and AWS/Azure enterprise integration patterns.
Experience managing managed service providers and offshore engineering teams.
AWS Solutions Architect (Professional), Certified Kubernetes Administrator, HashiCorp, or equivalent architecture or platform-engineering credentials.
Technical credibility demonstrated by staying close to code and architecture, contributing personally where judgment is required, and delegating effectively.

Responsibilities

Define and own coding, testing, security, DevOps, CI/CD, and architectural standards across all five Plasma digital product domains.
Set and enforce the technical quality bar for internal teams, managed service providers, and external vendors.
Enforce engineering standards through the shared engineering platform, automated quality gates, and reviews of significant technical designs; personally review and approve significant designs.
Set and enforce integration standards, data architecture, and cross-product technical decisions across the Plasma digital ecosystem.
Serve as the formal interface with CSL Enterprise Architecture, establish engagement cadence, represent Plasma architecture, and bring enterprise decisions back to Plasma.
Manage and develop the Plasma Business Architect and delegate routine architecture work to domain technical leads with clear guardrails.
Own the target-state architecture for the Data Backbone.
Provide direct people leadership for cross-domain enabling functions, including architecture, QA, AI/ML, automation, data, SRE/DevOps, and UX roles.
Own hiring standards, role design, career development frameworks, and succession planning for the cross-domain engineering team; personally interview technical leads among broader Plasma technology hires.
Foster technical excellence, accountability, psychological safety, and continuous learning.
Own the engineering tooling, platform, and capability roadmap, including Data Backbone architecture, middleware integration standards, cloud infrastructure direction, and the DevOps toolchain, in conjunction with enterprise capability owners.
Anticipate platform capability needs 12–24 months ahead and evaluate build-versus-buy-versus-partner decisions, making technology investment recommendations to senior leadership.
Own the shared engineering platform and its roadmap, approve its architecture, and review its highest-risk design decisions.
Review and approve technical approaches for significant architectural decisions across Plasma digital products and vendor solutions; serve as escalation authority for technical quality issues.
Establish technical health and developer experience measures, including code quality, test coverage, lead time, deployment frequency, change failure rate, MTTR, onboarding and environment setup time, and developer satisfaction.
Adapt engineering quality gates as AI coding assistants generate more code, ensuring review depth, test coverage, and traceability scale appropriately.
Establish and execute AI and Generative AI strategy for engineering; identify opportunities to accelerate delivery, improve quality, and enable business capabilities.
Drive adoption of AI-assisted software development practices, including code generation, testing and documentation automation, and developer productivity tools.
Partner with business stakeholders, data teams, enterprise architecture, and security teams to identify, prioritize, and deliver AI-enabled solutions.
Ensure AI solutions meet enterprise governance, regulatory, privacy, data protection, and responsible AI standards.
Own operational discipline for AI in production, including model evaluation, evaluation harnesses, observability and monitoring, prompt and version management, guardrails, red-teaming, and inference and GPU cost management; establish reusable capabilities across AI products and use cases.
Establish and own the formal matrix relationship with CSL Cyber for security and compliance standards across Plasma digital products.
Embed healthcare data protection, GDPR, and cloud security posture requirements in engineering standards.
Oversee regulatory compliance engineering for applicable frameworks, including 21 CFR Part 11, HIPAA, GxP, and EU Annex 11.
Embed security controls and regulated defaults in the shared engineering platform so they apply to new services by construction.