Vice President of Software Engineering

Primary Responsibilities

Engineering Leadership and Organization Development
Lead Magna's software engineering organization across multiple products and lines of business.
Develop and coach engineering managers, senior technical leaders, and individual contributors, establishing clear accountability and high performance at every level.
Assess and evolve organizational structure, team capacity, role clarity, and leadership coverage as the portfolio grows.
Own workforce planning, hiring, onboarding, performance management, succession planning, career development, the engineering budget, and vendor and contractor relationships for software engineering.
Build a culture of ownership, collaboration, continuous improvement, and direct, respectful communication.
Balance durable product alignment with the ability to shift talent across shared components, high-priority initiatives, and changing business needs.
Delivery and Operational Excellence
Translate company, product, and business-line priorities into clear engineering roadmaps, staffing plans, and execution commitments.
Establish a consistent operating cadence for planning, prioritization, estimation, delivery, release management, and executive reporting.
Improve the predictability, speed, and transparency of software delivery while maintaining appropriate quality and risk controls.
Proactively identify dependencies, resource constraints, delivery risks, and organizational blockers, and drive them to resolution.
Define and monitor meaningful engineering measures related to delivery, quality, reliability, security, and team health.
Ensure teams own software throughout its lifecycle, from problem definition and design through deployment, monitoring, support, incident response, and ongoing improvement.
Software Quality and Technical Execution
Guide the pragmatic modernization of legacy applications while protecting business continuity and customer experience.
Lead the technical integration of acquired businesses and platforms into Magna's shared capabilities.
Raise standards for software design, code quality, automated testing, observability, documentation, maintainability, and production readiness.
Strengthen engineering practices across APIs, cloud services, distributed systems, CI/CD, infrastructure as code, and secure software development.
Ensure software meets the security, privacy, and compliance obligations that come with handling protected health information, personal data, and privileged legal material, including [HIPAA, SOC 2, and client security audits – confirm].
Ensure teams make practical technology choices that fit the needs of each product while supporting appropriate reuse, interoperability, and shared platform capabilities.
Maintain enough technical depth to evaluate tradeoffs, challenge assumptions, support incident resolution, and earn credibility with senior engineers and architects.
Cross-Functional and Executive Partnership
Partner with Product and Design to create achievable roadmaps, clarify requirements, and balance customer value, technical health, and delivery capacity.
Work closely with business, operations, and go-to-market leaders to translate legal services workflows and client needs into scalable software capabilities.
Communicate plans, tradeoffs, risks, progress, and outcomes clearly to executive and nontechnical stakeholders.
Create effective feedback loops between engineering teams and the internal users, clients, and business stakeholders who depend on Magna's products.
AI-Enabled Engineering and Product Development
Advance the responsible use of AI-assisted development tools to improve engineering productivity, quality, documentation, testing, and knowledge sharing.
Partner with Product, the CTO, and technical leaders to evaluate and deliver practical AI and large-language-model capabilities within Magna's products and workflows, such as transcript summarization, deposition indexing, and medical record review.
Establish appropriate engineering discipline around AI-enabled features, including evaluation, security, privacy, reliability, human oversight, and ongoing monitoring.
Encourage thoughtful experimentation while ensuring AI investments remain connected to measurable customer and business outcomes.

What Success Looks Like in the First 12 Months

A predictable planning and release cadence, with delivery commitments met and reported transparently to executive leadership.
A clear organizational design with strong leadership coverage across products and shared platforms.
Measurable progress on Recordtrak and Maggie without disruption to clients.
At least one AI-enabled capability in production with defined evaluation, monitoring, and human oversight.

Required Qualifications

12+ years of progressive software-engineering experience, including 5+ years leading multiple teams or product areas.
Demonstrated success building and leading high performing software engineering organizations, including managing managers.
Track record of delivering complex, business-critical software while improving execution discipline, quality, and predictability.
Strong understanding of modern software architecture, APIs, cloud platforms, distributed systems, CI/CD, observability, security, and production operations.
Experience modernizing legacy systems incrementally while continuing to meet active business and customer commitments.
Ability to lead effectively across a varied technology portfolio. Magna's core platforms are built primarily on Microsoft technologies (C#, .NET, Azure); working knowledge of this stack and of modern web, cloud, and data technologies is expected.
Strong organizational judgment, including the ability to make sound decisions about team design, capacity, prioritization, and technical investment.
Exceptional written and verbal communication skills, with the ability to translate between technical, operational, and commercial audiences.
Demonstrated ability to partner effectively with senior architects and principal-level technical experts while maintaining clear decision rights and accountability.
Bachelor's degree in computer science, engineering, or related field (or equivalent practical experience).
Preferred Qualifications
Experience delivering AI- or machine-learning-enabled products or meaningfully integrating AI into the software-development lifecycle.
Experience building software subject to HIPAA, SOC 2, or similar regulatory and client security requirements.
Experience in a multi-product, multi-business-line, professional service, legal services, private-equity-backed, or acquisition-oriented environment, including integrating acquired technology platforms and teams.
Leadership Profile
The successful candidate will be:
Business-minded: Connects engineering work to customer outcomes, operational needs, and company priorities.
Execution-oriented: Creates clarity, establishes accountability, and follows through on commitments.
Technically credible: Understands complex systems and tradeoffs without becoming a bottleneck or displacing technical owners.
People-centered: Develops leaders, creates healthy teams, and gives clear and actionable feedback.
Pragmatic: Balances modernization, speed, quality, and risk based on business context.
Collaborative: Works effectively across functions and business lines and communicates with candor and respect.
Adaptable: Leads confidently through changing priorities, evolving technologies, and organizational growth.