Head of Software Engineering

The Fedcap Group•REMOTE, United States

11d

About The Position

The Head of Software Engineering serves as the enterprise leader for application engineering strategy, systems integration architecture, DevOps execution, automation, and AI-enabled solution development across The Fedcap Group. This role advances and scales an established engineering function to ensure enterprise-developed applications, integrations, and intelligent automation capabilities are secure, scalable, innovative, compliant, and aligned with enterprise architecture and governance standards across a geographically distributed organization. As the organization continues to expand across regions and service lines, the Head of Software Engineering will accelerate modernization, reduce technical fragmentation, embed AI-driven capabilities into enterprise workflows, and position engineering as a strategic driver of operational excellence and innovation. Reporting to the SVP, Enterprise Systems & Digital Platforms, this leader partners closely with IT Infrastructure & Operations, Security, Data & Analytics, and operating leadership to ensure engineering practices are standardized, performance-driven, resilient, financially disciplined, and aligned with enterprise governance requirements.

Requirements

10+ years of progressive leadership in software engineering and enterprise application environments.
Demonstrated expertise in secure SDLC advancement, DevOps optimization, and API-first architecture.
Experience leading distributed onshore, nearshore, and offshore engineering teams.
Experience implementing automation and AI-enabled capabilities within enterprise systems.
Experience modernizing legacy systems in distributed, multi-entity organizations.
Experience operating in regulated environments.
Proven ability to scale engineering capabilities while maintaining financial discipline.
Strong executive communication and cross-functional leadership skills.

Nice To Haves

Lead with engineering discipline and innovation orientation.
Balance speed, quality, scalability, compliance, and cost efficiency.
Build structured governance while fostering a culture of modernization and creativity.
Drive responsible AI-enabled transformation aligned with enterprise strategy.
Operate as a strategic partner within an enterprise governance model.

Responsibilities

Define and evolve enterprise application architecture standards.
Establish consistent development frameworks and approved technology stacks.
Lead modernization of legacy applications while enhancing scalability and maintainability.
Identify and prioritize opportunities to embed automation and AI-enabled decision support within enterprise workflows.
Drive rationalization of redundant custom solutions across business units.
Evaluate emerging technologies and pilot innovation initiatives aligned with enterprise strategy.
Establish structured intake and prioritization processes for engineering initiatives.
Align development roadmaps with enterprise portfolio governance and strategic objectives.
Ensure engineering resources are allocated to the highest-value initiatives.
Prevent proliferation of unauthorized, redundant, or non-strategic custom solutions.
Partner with Systems leadership to ensure build-versus-buy decisions are financially and strategically justified.
Advance existing SDLC governance to improve consistency, automation, and measurable quality outcomes.
Optimize requirements management, code review, testing, and documentation standards.
Govern version control, branching strategies, and release management protocols.
Maintain formal Dev/Test/Production controls with disciplined change management.
Ensure audit-ready engineering documentation aligned with compliance requirements.
Mature CI/CD pipelines to enhance deployment reliability and scalability.
Introduce measurable engineering productivity and quality benchmarks.
Implement AI-assisted development tools where appropriate to enhance developer efficiency and code quality.
Define application monitoring, logging, and observability standards.
Improve deployment consistency while enabling faster innovation cycles.
Govern API standards and modern integration architecture patterns across systems.
Replace legacy point-to-point integrations with scalable API-first models.
Expand workflow automation and RPA initiatives with measurable operational impact.
Partner with Data & Analytics to embed predictive models and AI-enabled insights into operational systems.
Ensure responsible, secure, and governed implementation of AI-enabled application features.
Maintain disciplined oversight of automation and AI experimentation to prevent fragmentation.
Embed secure coding standards and shift-left security practices.
Partner with Security to maintain strong vulnerability remediation performance.
Ensure engineering alignment with HIPAA, SOC 2 Type II, ISO 27001, and other required control frameworks.
Support audit evidence production for application development controls.
Ensure identity and role-based access enforcement is consistently implemented in application design.
Lead application and integration due diligence assessments for acquisitions.
Execute standardized application integration during entity onboarding.
Ensure engineering readiness for geographic expansion and new program launches.
Support enterprise system consolidation aligned with modernization strategy.