Software Engineering Delivery & Platform Enablement

Summary

Join RxSense as a Senior Vice President of Software Engineering Delivery & Platform Enablement to lead the execution of software and service delivery and build the foundation for internal engineering excellence. Drive outcomes across project delivery, DevOps, platform maturity, core services, AI adoption, and team capability development. Bring structure, innovation, and accountability to value delivery and scaling technical capabilities. Provide focused leadership for platform services, automation, and internal tools. Integrate AI into software development workflows, platform services, and tooling, empowering software delivery teams to integrate AI and machine learning capabilities into their solutions. Define architectural patterns, reusable services, and technical governance models. Lead the transformation to a product-oriented engineering culture and implement technical upskilling and mentorship programs.

Requirements

• 20+ years of experience in software engineering, with 7 plus years in senior or executive leadership roles driving delivery, platform, and DevOps strategy across large-scale systems
• Proven track record of leading complex software delivery organizations in fast-paced, high-growth environments — ideally within SaaS, healthcare technology, or enterprise platforms
• Deep expertise in cloud-native architecture, agile development methodologies, and mature DevOps practices, with hands-on leadership of CI/CD pipelines, infrastructure automation, observability, and developer tooling
• Demonstrated success in designing and scaling internal developer platforms, reusable services, and integration frameworks across multiple product lines or business units
• Strong experience with AI and machine learning integration into both internal engineering workflows (e.g., AI-assisted coding, QA, observability) and customer-facing product delivery
• Proven ability to enable and upskill delivery teams to confidently incorporate AI/ML capabilities into solutions, with a strong grasp of responsible and ethical AI usage
• Experience with technical architecture governance, platform maturity models, and alignment of cross-functional engineering teams
• Exceptional leadership, strategic thinking, and communication skills with a bias for action and transformation
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field; MBA or equivalent cross-functional leadership experience is a plus

Responsibilities

• Lead strategy and execution for automation across CI/CD, infrastructure as code, testing, observability, and developer productivity tooling
• Build and scale internal developer platforms and shared services to accelerate delivery velocity and reduce operational friction
• Identify and implement opportunities to embed AI and machine learning into internal tooling, code review, testing, observability, deployment pipelines, and incident management processes
• Champion the adoption of AI-assisted developer workflows, including intelligent documentation generation, prompt-based coding assistants, and automated quality assurance
• Partner with Software Engineering leaders to enable delivery teams to embed AI and ML capabilities directly into the solutions they build, including integration patterns, data pipeline readiness, and AI-driven product features
• Ensure platform services, integration tools, and foundational capabilities have clear ownership, support, and room to evolve
• Strengthen DevOps as a core enabler of product delivery — distinct from BI/reporting functions — ensuring it is staffed, funded, and directed with long-term vision
• Collaborate with Product and Architecture to align platform and tooling strategy with emerging AI/ML use cases and customer value drivers
• Define and champion architectural patterns, reusable services, and technical governance models across the engineering organization
• Collaborate with senior architects to realign them to their highest areas of impact — particularly in scalable, performant solution design and integration strategy
• Own the maturity roadmap for core services and integration platforms, identifying gaps and driving investment decisions accordingly
• Guide the design and adoption of AI-enhanced architectures and integration frameworks that support continuous learning and adaptive system behavior
• Lead the transformation to a product-oriented, technically strong engineering culture
• Design and implement technical upskilling and mentorship programs, including training on AI-powered development tools, prompt engineering, and ethical use of generative AI
• Foster organizational readiness across delivery teams to confidently build, deploy, and manage AI/ML features in customer-facing and internal solutions
• Create a culture of ownership, autonomy, and accountability across delivery and platform teams, with a strong emphasis on continuous learning and responsible innovation

Preferred Qualifications

Strong understanding of healthcare data ecosystems, interoperability standards, APIs, and regulatory environments (e.g., HIPAA, HITRUST) is preferred