Sr. Manager, Software Engineering

Visa•Austin, TX

10d•$163,300 - $261,600•Hybrid

About The Position

We are seeking a highly technical and hands-on Senior Manager, Software Engineering to lead high-performing engineering teams responsible for designing, developing, and operating large-scale distributed systems. This role requires a technology leader who combines deep software engineering expertise with strong people leadership and extensive experience in Artificial Intelligence technologies, including Generative AI, Large Language Models (LLMs), AI Agents, Claude Code, Codex, GitHub Copilot, Retrieval-Augmented Generation (RAG), and modern AI-native development practices. The ideal candidate is passionate about solving complex engineering challenges, scaling organizations, mentoring future leaders, and driving innovation through AI-powered software development. You will work closely with product, architecture, security, infrastructure, and business teams to create next-generation payment and commerce solutions that serve millions of users globally.

Requirements

8+ years of relevant work experience and a Bachelors degree, OR 11+ years of relevant work experience
9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
10+ years of software engineering experience with 3+ years leading engineering teams.
Experience in reviewing business requirements and developing technical documentation.
Experience in designing and implementing testing procedures for APIs and integration patterns.
Experience in participating in design reviews and providing input on product designs and schedules.
Experience in leading teams to ensure productivity and high-quality delivery.
Experience in code review and accountability for development/testing activities.
Experience in technical evaluations and proof of concepts for new technologies.
Experience building large-scale transaction processing, e-commerce, fintech, payments, or highly regulated platforms.
Experience implementing enterprise AI platforms and AI-powered developer productivity solutions.
Deep knowledge of Generative AI ecosystems, LLM operations, prompt engineering, RAG, vector databases, and AI agents.
Experience with modern AI-assisted software development platforms including Claude Code, Codex, GitHub Copilot, Cursor, and related technologies.
Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field preferred.
Demonstrated track record of delivering large transformational initiatives that create measurable business impact.

Nice To Haves

You are equally comfortable discussing distributed systems architecture with senior engineers, presenting technology strategy to executives, mentoring engineering managers, and rolling up your sleeves to prototype AI solutions.
You thrive in environments where innovation, scale, AI transformation, and technical excellence converge to solve some of the world's most complex engineering challenges.

Responsibilities

Lead and grow teams responsible for designing and delivering highly scalable, resilient, and secure software platforms operating at global scale.
Drive technical strategy and execution across distributed systems, cloud-native architectures, APIs, AI-enabled platforms, and mission-critical payment systems.
Build and cultivate a high-performance engineering culture focused on quality, operational excellence, innovation, and customer obsession.
Architect and oversee the development of large-scale applications capable of supporting millions of daily transactions while meeting stringent availability and security requirements.
Champion AI-first engineering practices by leveraging Generative AI, Agentic AI frameworks, LLMs, Claude Code, Codex, GitHub Copilot, and AI-powered SDLC automation.
Partner with product and business leaders to define roadmaps and translate strategic priorities into executable engineering initiatives.
Lead modernization efforts involving cloud platforms, microservices, event-driven architectures, MLOps, and AI infrastructure.
Establish engineering metrics, delivery frameworks, and operational practices that improve velocity, quality, reliability, and developer productivity.
Drive innovation through proof-of-concepts, experimentation, and adoption of emerging technologies that create measurable business value.
Mentor engineers, architects, and engineering managers while fostering a culture of technical excellence and continuous learning.
Lead cross-functional initiatives involving security, compliance, AI governance, resiliency, observability, and platform engineering.
Influence organizational strategy through technology leadership, technical vision, and executive stakeholder engagement.
Provides strategic technology leadership and serves as the technical authority for large-scale application platforms and distributed systems.
Leads teams through architecture design, technology selection, platform modernization, and enterprise-scale engineering initiatives.
Establishes engineering standards, AI governance frameworks, and software development best practices across multiple teams.
Drives adoption of AI-powered engineering tools and workflows to accelerate software delivery and improve developer experience.
Evaluates, designs, and implements solutions utilizing Generative AI, Large Language Models, Agentic Frameworks, MCP, RAG, Vector Databases, and AI orchestration platforms.
Partners with executive leadership, product management, and business stakeholders to align technology investments with strategic company objectives.
Builds and executes long-term technology roadmaps while maintaining operational stability and service reliability.
Leads technical reviews, architecture governance, and decision-making processes for mission-critical systems.
Champions platform resiliency, security-by-design principles, compliance requirements, and operational excellence.
Guides engineering organizations in building reusable frameworks, services, SDKs, and AI-enabled platform capabilities.
Establishes key engineering KPIs related to availability, scalability, performance, quality, developer productivity, and business outcomes.
Drives recruitment, talent development, succession planning, and leadership growth across engineering teams.
Identifies emerging industry trends and evaluates opportunities to leverage new technologies for business transformation.