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Leads software engineering and site reliability efforts, delivering secure, scalable production systems. Responsibilities include system design, coding, testing, troubleshooting, automation of recurring remediation, operational stability, vendor architecture evaluations, and adoption of AI-assisted engineering practices with strong validation, security, and responsible-use standards.

Lead the transformation of Payments Production Management into a mature SRE organization. Build and manage a centralized program function, establish governance and operating standards, develop a transformation roadmap, and coordinate cross-functional execution across engineering, operations, risk, and product teams. Track reliability metrics, improve incident and change management, reduce toil, expand automation, and deliver executive reporting. Lead AI-assisted production operations practices with human validation, security awareness, and auditability.

Supports product discovery, development, and optimization for the Deposit 2.0 team. Conducts user research, journey mapping, market analysis, and customer feedback collection to identify opportunities and inform the product roadmap. Tracks product metrics related to time, cost, and quality, considers broader customer experience implications, and writes requirements, epics, and user stories. Collaborates with Product Managers and cross-functional teams using analytical and Agile product development practices.

Manages a portfolio of 100–130 small-business clients, providing customized banking, deposit, cash management, credit, and financial advisory solutions. Responsibilities include acquiring and retaining clients, developing relationships through in-person meetings, identifying business opportunities, managing risk, supporting branches, and connecting clients with specialists. The role requires business lending knowledge, strong communication, prioritization, client service, regulatory compliance, and proficiency with Microsoft Office tools.

Leads the architecture, delivery, reliability, and modernization of large-scale market data infrastructure. Owns production health, observability, capacity, resilience, cloud migration, automation, incident response, and root-cause analysis. Provides technical leadership through mentoring, engineering standards, stakeholder governance, and remediation oversight. Requires advanced Python and Linux expertise, low-latency networking knowledge, cloud infrastructure experience, and hands-on market data distribution and trading-platform support.

Leads multiple software engineering departments and technical domains supporting payment network processing. Owns architecture for authorizations, tokenization, disputes, fraud, identity, settlement, and related data flows. Establishes scalable, secure, compliant engineering standards and directs cloud-native modernization. Drives enterprise adoption of agentic AI-enabled engineering, SDLC automation, governance, testing, resilience, and incident response practices. Influences executives and cross-functional stakeholders while managing large technical organizations, complex projects, talent development, and operational stability.

Lead end-to-end brand and campaign strategy for the Olympic and Paralympic sponsorship: translate rights into creative platforms, manage paid media and measurement, coordinate agencies and internal teams, oversee timelines, budgets, and stakeholder alignment, and create executive presentations and measurement frameworks.

Leads solutions analysis and technical program delivery by translating business and data requirements into feasible technical solutions. Develops data models, analyzes complex datasets, integrates platforms and systems, and provides strategic insights for business initiatives. Acts as a subject matter expert, manages ambiguity and dependencies, mentors team members, and partners with product owners, business stakeholders, operations, and software developers. Applies data analytics, visualization, AI/ML tools, and technical writing to support informed decision-making.

Design, build, and deliver production AI/ML solutions using agile practices. Translate business requirements into ML specifications, produce secure high-quality code, create architecture artifacts, analyze large datasets, troubleshoot complex issues, and contribute to engineering communities and continuous improvement.

Support Technology, Product, and Operations teams through agile delivery using Scrum and Kanban. Facilitate ceremonies, decision-making, training, continuous improvement, release management, and blocker resolution. Use Jira queries, Excel pivot tables, analytics, dashboards, and reporting to identify delivery trends and communicate risks, progress, dependencies, and recommendations. Translate technical information into business language while coordinating multiple priorities and validating enterprise-authorized AI-assisted delivery artifacts.