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Visa

Runs a global network for digital payments

Chief Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeFoster City, CA, USA

About the Job

Requirements

  • At least 12 years of relevant work experience with a Bachelor’s degree, or at least 9 years of work experience with an advanced degree (such as a Master’s, MBA, JD, or MD), or 6 years of work experience with a PhD, or at least 15 years of relevant work experience.
  • A Bachelor’s degree in Computer Science or a related field is required; a Master’s degree or equivalent depth is preferred.
  • Demonstrated track record of shipping AI or machine learning systems that run in production at enterprise scale, rather than demos or isolated proof-of-concepts.
  • Deep fluency with modern generative AI stacks, including foundation model APIs, retrieval-augmented generation, vector search, tool use or function calling, agent orchestration, and evaluation frameworks.
  • Expert-level software craft, with Python required and strong additional experience in at least one of TypeScript, Java, or Go, as well as rigorous testing, observability, and API design.
  • Experience designing platforms used by other engineering teams, such as internal developer platforms or machine learning platforms.
  • Strong systems thinking across latency, reliability, cost, data lineage, identity and authentication, secrets, and failure modes of probabilistic systems.
  • Ability to operate in a regulated industry such as financial services, payments, or healthcare.
  • Experience in payments, commerce, fraud or risk, identity, or large-scale transaction systems.
  • Hands-on work with agent frameworks such as LangGraph or equivalent, MCP-style tool protocols, and multi-agent patterns.
  • Machine learning operations or large language model operations platform experience, including feature stores, model registries, experiment tracking, and online/offline evaluation pipelines.
  • Prior ownership of AI governance engineering, including policy-as-code, access minimization, personally identifiable information handling, model cards, and audit trails.
  • Experience standing up forward-deployed or tiger-team models that embed with business domains.

Responsibilities

  • Define the technical roadmap for AI software platforms and agentic capabilities, aligned with business outcomes.
  • Architect, lead the design of, and hands-on build flagship agentic systems.
  • Establish large language model operations and artificial intelligence operations practices, including evaluations as tests, tracing, cost telemetry, drift detection, model and prompt versioning, and service-level objectives for AI services.
  • Set coding, testing, and review standards for AI-adjacent software, including Python and TypeScript services, APIs, data pipelines, and infrastructure as code.
  • Build and mentor a high-leverage bench of staff and principal engineers and AI tiger-team leads, and operate as a player-coach on the hardest problems.
  • Partner with security, privacy, risk, and legal teams to implement responsible AI controls for a regulated payments and financial technology environment.
  • Drive build-versus-buy decisions across foundation models, vector stores, orchestration frameworks, and evaluation tooling.
  • Represent engineering in executive forums and translate technical risk, readiness, and investment into actionable leadership decisions.
  • Track frontier models and research, and assess their production suitability, vendor lock-in, and total cost of ownership.
  • Design enterprise AI software architecture, including reference designs for large language model applications, multi-agent workflows, retrieval-augmented generation and grounding, tool use, and hybrid classical machine learning and generative AI systems.
  • Build production-grade AI platforms and shared services for model access, retrieval, evaluation, observability, prompt and version management, feature and store integration, and deployment.
  • Develop agentic systems at scale, including orchestration, memory, tool calling, human-in-the-loop controls, and safe autonomous workflows across business domains.
  • Establish AI quality and safety systems, including evaluation harnesses, red-teaming, bias and privacy checks, policy enforcement, rollback, canary releases, and incident response for AI services.
  • Improve developer experience for AI through software development kits, templates, continuous integration and continuous delivery, golden paths, and inner-loop tooling.
  • Set technical strategy and standards for model selection, cost and latency tradeoffs, data contracts, API design, and architecture reviews for high-risk AI systems.
  • Partner with product, risk, compliance, legal, security, and domain engineering teams to move use cases from prototype to regulated production.

Desired Qualifications

  • At least 15 years of experience with a Bachelor’s degree, or 12 years of experience with an advanced degree (such as a Master’s, MBA, JD, or MD), or a PhD with at least 9 years of experience.
  • Experience in payments, commerce, fraud or risk, identity, or large-scale transaction systems.
  • Open-source contributions, internal platform adoption metrics, or published technical writing used by other engineers.

About the Company

Visa

Runs a global network for digital payments

Visa runs a global payment network that connects banks, merchants and consumers so card purchases and money transfers move between financial institutions. Its VisaNet system handles authorization, clearing and settlement, linking the bank behind a buyer's card with the bank that accepts a merchant's payment. The company earns fees from payment activity, transaction processing and international transactions, and sells fraud prevention tools, payment software and consulting services to businesses. Banks and other partners issue Visa branded cards and use its technology to build their own payment products. Visa traces its roots to a Bank of America card program launched in 1958 and is headquartered in San Francisco.

Company size
10,001+
Company stage
N/A
Total funding
$24.2M
Headquarters
San Francisco, CA
Founded
1958

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