Director, Software Delivery Architecture

SMBC•Charlotte, NC

3d•Hybrid

About The Position

SMBC is seeking a Director, Software Delivery Architecture to lead the strategy, architecture, governance, and continuous evolution of enterprise software delivery capabilities. The role defines and governs Secure Software Development Lifecycle (SSDLC) and DevSecOps practices, developer platforms, engineering tooling, and AI-enabled software delivery capabilities. It helps define enterprise platform standards, reference architectures, implementation patterns, engineering roadmaps, and technology strategies to enable secure, scalable, resilient, and efficient software delivery across the organization. The Director will drive engineering transformation initiatives to improve software quality, developer productivity, operational resilience, regulatory compliance, and business outcomes. A key focus is identifying and implementing AI opportunities throughout the software delivery lifecycle to improve quality, reduce manual effort, accelerate delivery, and strengthen engineering governance. The role combines modern architecture practices, platform engineering, AI-enabled development capabilities, and enterprise governance to help shape SMBC’s software engineering strategy. SMBC uses a hybrid workforce model that allows employees to work from home and from an SMBC office. Employees must live within a reasonable commuting distance of their office location. Candidates will learn the specific hybrid schedule during the interview process; hybrid work may not be permitted for certain roles.

Requirements

10+ years of progressive experience in Software Engineering, Enterprise Architecture, Platform Engineering, DevOps, DevSecOps, Software Delivery, or related technology leadership roles.
Experience designing and implementing AI-enabled engineering solutions using Python, GenAI frameworks, LLM technologies, vector databases, retrieval architectures, and enterprise AI platforms such as Azure AI Services, Azure AI Search, Databricks, OpenAI, or equivalent technologies.
Demonstrated experience leading enterprise-wide transformation initiatives involving application modernization, platform engineering, DevSecOps, software governance, or AI adoption programs.
Experience developing enterprise standards, architecture patterns, architecture roadmaps, and target-state strategies.
Strong understanding of SDLC, SSDLC, Agile delivery, DevSecOps, CI/CD, software architecture, and platform engineering practices.
Experience identifying and implementing AI, automation, or developer productivity solutions within technology organizations.
Experience within banking, financial services, or other highly regulated industries.
Knowledge of NIST Secure Software Development Framework (SSDF), software supply chain security practices, DevSecOps frameworks, and AI governance principles.

Nice To Haves

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline.
TOGAF, AWS or Azure Architecture certifications, SAFe, CISSP, CSSLP, or comparable industry certifications.

Responsibilities

Define and maintain the enterprise Software Delivery Architecture strategy, roadmap, target-state architecture, operating model, standards, and reference architectures.
Establish governance frameworks, architecture standards, and implementation patterns for SSDLC, DevSecOps, platform engineering, and software governance.
Establish reference architectures, patterns, and best practices for software development, testing, deployment, and release management.
Establish platform standards for source control, CI/CD, testing, software quality, security scanning, and deployment automation.
Provide architectural oversight for development platforms and tools, including source control, CI/CD, testing, artifact management, and collaboration platforms.
Drive modernization initiatives that improve delivery velocity, software quality, security, resiliency, and developer experience.
Partner with Enterprise Architecture, Engineering, Cybersecurity, Data, and Risk teams to align software delivery capabilities with business and technology objectives.
Evaluate emerging engineering technologies, industry trends, and software delivery practices; recommend enterprise adoption, standardization, optimization, or retirement.
Assess engineering processes and development workflows to identify automation and AI-driven opportunities across all phases of the SDLC that improve speed, quality, security, and efficiency.
Evaluate, pilot, and lead implementation of AI-powered engineering solutions that improve developer productivity and delivery outcomes.
Lead tooling rationalization, consolidation, and optimization efforts to maximize business value and reduce platform complexity.