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 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 Enginee… ... 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, the 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, SOC2 TypeII, ISO27001, 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 (First12Months) 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. #J-18808-Ljbffr