Head of Software Engineering
Position Summary 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. Mission To deliver secure, scalable, intelligent, and cost-effective enterprise applications that strengthen mission delivery, enable automation and data-driven decision-making, reduce system fragmentation, and support sustainable organizational growth. Scope of Accountability The Head of Software Engineering is accountable for:
- Enterprise software development standards and advanced SDLC governance
- Application architecture patterns and approved engineering frameworks
- API and enterprise integration architecture standards
- DevOps pipelines, release automation, and engineering productivity optimization
- Application performance monitoring and operational observability standards
- Technical debt prioritization and modernization acceleration
- Automation platforms (RPA, workflow engines, low-code governance)
- AI-enabled application capabilities embedded within enterprise systems
- Intelligent workflow and decision-support integration in collaboration with Data & Analytics
- Engineering documentation and configuration discipline
- Secure coding practices and vulnerability remediation coordination
- Application lifecycle management and decommissioning governance
- Engineering vendor lifecycle management
- Engineering budget management and cost discipline
- Build-versus-buy analysis and financial justification of custom development initiatives
- Engineering capacity planning, delivery forecasting, and productivity optimization
- Application components of acquisition integration and enterprise platform consolidation
- Implementation of security control requirements
- Leadership of distributed onshore, nearshore, and offshore engineering teams
Core Responsibilities Application Strategy, Architecture & Innovation
- 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.
Engineering Portfolio & Demand Governance
- 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.
Software Development Lifecycle (SDLC) & Engineering Maturity
- 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.
DevOps, Release Management & Engineering Productivity
- 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.
Enterprise Integration, Intelligent Automation & AI Enablement
- 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.
Application Security & Compliance Alignment
- 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.
Acquisition Integration & Expansion Enablement
- 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.
Success Metrics (First 12 Months)
- Measurable advancement in engineering maturity, deployment reliability, and release predictability across enterprise applications.
- Reduction of prioritized technical debt while maintaining operational stability.
- Expansion of intelligent automation and AI-enabled capabilities with documented operational impact.
- Standardized integration architecture adopted across major enterprise platforms.
- Demonstrated financial discipline through optimized engineering spend and justified build-versus-buy decisions.
- Engineering organization strengthened across onshore, nearshore, and offshore teams to support modernization and enterprise scale.
Qualifications
- 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.
Leadership Profile The ideal candidate will:
- 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.
Mission & Stewardship Commitment
- Ensure enterprise applications protect client data and enable intelligent decision-making.
- Advance engineering capabilities that directly strengthen frontline impact.
- Promote responsible innovation and ethical AI implementation.
- Deliver secure, scalable, and financially responsible systems that support mission growth across all operating entities.
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