Staff Software Engineer (AI Engineer)

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 Role Summary: We are seeking a Staff AI Engineer to help build next-generation cybersecurity AI products for enterprise security teams. This is a hands-on individual contributor role for an engineer who combines strong AI engineering capability, practical software development skills, and a strong interest in cybersecurity. You will report to the Director, Cybersecurity AI Product and work as part of a newly formed product development team focused on building and operating agentic solutions that help users investigate threats, triage alerts, automate security workflows, analyze vulnerabilities, and make better security decisions. The ideal candidate is AI-native, product-minded, proactive, and comfortable working through ambiguity. You should be able to learn quickly, experiment with new AI technologies, build reliable product features, and translate customer problems into practical AI-driven solutions. This role requires hands-on experience with LLM applications, agentic AI systems, retrieval-augmented generation, tool orchestration, context management, model evaluation, cloud-native software engineering, APIs, and secure software development. Familiarity with cybersecurity concepts, security operations, cloud security, or threat intelligence is strongly preferred. Key Responsibilities: • Design and Build Advanced Cybersecurity AI Products • Build agentic AI workflows for various cybersecurity operations, engineering, and risk processes. • Convert ambiguous product ideas and early prototypes into secure, maintainable, production-grade AI systems • Take end-to-end Technical Ownership of Complex AI Product Components, from problem framing to production operation. • Break down ambiguous problems into technical plans, milestones, risks, and deliverables • Contribute to technical roadmaps and influence prioritization through evidence, customer feedback, and engineering principles • Identify design gaps, tech-debts, scalability risks, and make sound engineering trade-offs. • Research, Evaluate, and Operationalized Emerging AI Technologies • Continuously Learn, Research and Evaluate Emerging AI technologies • Translate research findings into practical implementation patterns, product features, internal recommendations, or technical standards • Share findings through technical documentation, demos, internal talks or fast POCs • Build Production-Grade AI Products • Develop backend services, APIs, integrations, AI orchestration, data pipelines, and other software components. • Support deployment, monitoring, debugging, and operational support of AI products • Work with CI/CD pipelines, containers, infrastructure as code, logging, metrics, and automated testing • Design systems that scale across customers, workloads, data sources, and platforms • Influence Through Technical Excellence • Provide technical guidance to other engineers through code reviews, design discussions, documentation, and example implementations • Mentor less experienced engineers informally through strong engineering practice and clear reasoning • Raise the quality of team decisions by bringing evidence, research, customer context, and practical trade-off analysis • Communicate complex AI, security, and architecture concepts clearly to technical and non-technical stakeholders • Collaborate with product, security, solution engineering, and customer-facing teams to ensure product capabilities address real customer workflows • Demonstrate ownership, proactiveness, customer obsession, and ability to operate effectively in ambiguity Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Required Qualifications: Experience • 5+ years of professional experience in AI engineering and software engineering. • 3+ years of hands-on experience building AI/ML, LLM-based, automation, data-driven, or intelligent software systems. • Experience building production software, not only prototypes or notebooks. • Experience working in product engineering teams or delivering customer-facing technical solutions. AI Engineering: • Strong practical experience with LLM applications, AI workflow automation, AI assistants, copilots, or agentic AI systems. • Familiarity with concepts such as: • Prompt engineering • System prompts and instruction design • Retrieval-augmented generation • Vector search • Embeddings • Tool calling • Function orchestration • Context management • Agent memory • Evaluation datasets • Model benchmarking • Feedback loops • Experience with agentic AI frameworks or tools such as: • LangChain • LlamaIndex • Semantic Kernel • AutoGen • CrewAI • Vector databases • Knowledge graphs • Model evaluation frameworks • Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost. • Experience using commercial or open-source AI models and APIs. • Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement. Software Engineering: • Strong programming ability in two or more languages such as: • Python • TypeScript / Node.js • Go • Java • Rust • Strong understanding of software architecture, API design, data modeling, distributed systems, asynchronous processing, observability, and maintainability • Experien…