About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
Visa Resolve Online is looking for a leader to define guide and implement strategies, policies, and tools for next level of delivery maturity for VROL platform. We believe that the role is essential in integrating the project functions and resources across the product life cycle, right from planning, building testing and deployment to support. You will lead the development of next-generation AI solutions that transform dispute management through Generative AI, Machine Learning, Conversational AI, Intelligent Document Processing, and Developer Productivity tools.
Reporting to Senior Director, you will need to strategize, implement, and communicate necessary process, workflows, and tools to enable developers code and test functional and technical changes at a consistent pace. As an Engineering Director you will lead a high‑performing software engineering team responsible for building, modernizing, and supporting Visa’s revenue‑related enterprise applications. You will define technical direction, champion the adoption of AI‑driven engineering practices, own architectural strategy, elevate engineering standards, and guide the delivery of secure, scalable, and resilient systems. This role requires a mindset to learn newer technologies and improvements in processes for a seamless and efficient delivery pipeline. In this role, you will bring deep technical and functional expertise, with a strong focus on leveraging AI both to accelerate development and to design intelligent solutions for complex business needs.
Responsibilities:
- Provides leadership, mentoring, guidance, and vision to groups of engineers engaged in building tools and services to achieve secure code and continuous flow of artifacts
- Support growth for people directly reporting by setting up clear expectations and goals; evaluating and managing KPIs and accountability
- Exhibit a growth mindset by adoption industry best practices and technology trends around information security practices in pursuit of continuous delivery
- Collaborate with cross-functional teams to identify opportunities for leveraging AI to drive business solutions.
- Oversee the design, development, and maintenance of Machine Learning models and solutions.
- Translating real-world business challenges into measurable machine learning metrics
- Explain complex algorithmic decisions and model predictions to non-technical stakeholders
- Maintain knowledge of current and emerging technologies or applications in areas of AI and Machine Learning
- Measure the effectiveness of AI initiatives and adjust strategies as needed
- Champion the use of AI across the engineering lifecycle, including AI assisted coding, automated testing, code generation, and productivity enhancing development workflows.
- Foster a culture of innovation, experimentation, and continuous improvement, encouraging teams to explore new technologies and evolve engineering standards.
- Understand, support, and enhance Agile practices around code integration, system thinking and scaled delivery
- Support multiple cross-functional agile teams in setting up test environments, build, deployment and troubleshooting. Collaborate with Tech leads in removing impediments hindering continuous delivery
- Comfortable to look under the hood and help the team troubleshoot issues around code, tools and workflows
- Work as the integration point of contact for internal and external infrastructure/ support teams by translating technical change requests to executable steps
- Keep track of changes requested by multiple development and testing teams for parallel code deployments
- Review, prioritize and schedule change requests in various environments starting from integration, member test and production
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager
Qualifications
Basic Qualifications:
- 10+ years of relevant work experience with a Bachelor’s Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.
Preferred Qualifications:
- Bachelor’s. degree with 12+ years, or M.S. degree with 10+ years, of experience designing, developing, and managing complex, enterprise‑class, mission‑critical global application systems.
- 5+ years leading engineering teams responsible for enterprise-scale software delivery
- Proven experience managing software delivery in an AI-enabled ecosystem, including adoption of AI-assisted engineering practices, productivity tools, and automation across the SDLC
- Strong technical foundation in Java and modern backend engineering, with experience in microservices, APIs, distributed systems, cloud-native architecture, Docker, and Kubernetes
- Hands-on experience with AI-assisted software delivery, including effective use of generative AI coding assistants and tools such as Claude Code CLI, GitHub Copilot, and Cline, along with prompt engineering, AI-supported code review, test generation, documentation, and productivity workflows.
- Ability to validate, refactor, and secure AI-generated code with strong human oversight, ensuring correctness, maintainability, performance, compliance, and production reliability.
- Working knowledge of AI/ML concepts, GenAI solutions, LLM-based applications, model evaluation, prompt engineering, RAG patterns, and responsible AI practices
- Knowledge of Agentic Skills and agent-based engineering workflows, including setting up, reviewing, and governing skills, skill repositories, and knowledge graphs to improve software delivery, documentation, and team productivity.
- Experience with Python and Machine Learning fundamentals, including preparing and analyzing data, building and evaluating predictive models, and improving model performance. Familiarity with common Machine Learning techniques such as regression, decision trees, random forests, and ensemble methods is beneficial. Experience using tools such as Python, scikit-learn, pandas, NumPy, and Jupyter notebooks is preferred. An understanding of model evaluation concepts (e.g., accuracy, precision, recall, and related metrics) is helpful
- Hands-on understanding of CI/CD, DevSecOps, automated testing, release management, observability, incident response, and production support for mission-critical platforms
- Ability to guide teams in reviewing, validating, securing, and governing AI-generated code or AI-assisted outputs before production use
- Experience with engineering toolchains such as Jira, Git/Bitbucket, Gradle, Jenkins, Maven, Artifactory, Liquibase, SonarQube, Checkmarx, Black Duck, or similar platforms
- Strong understanding of secure coding, application security, data privacy, governance, compliance, and risk management in AI-led software delivery
- Demonstrated ability to lead cross-functional Agile teams, remove delivery impediments, manage dependencies, and drive predictable execution across multiple parallel initiatives
- Strong people leadership skills, including coaching, mentoring, performance management, talent development, and building a culture of accountability, experimentation, and continuous learning
- Ability to translate business priorities into technical delivery plans and communicate clearly with senior stakeholders, product teams, architects, security, operations, and engineering teams
- Strong problem-solving mindset with the ability to navigate ambiguity, manage complex projects, make informed trade-offs, and drive measurable delivery outcomes
- Experience in the financial domain, payments industry, or other highly regulated technology environment is desirable
Visa is an EEO Employer
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
