Sw Engineer - Sr. Consultant Level

Visa Visa · Fintech · Bellevue, WA

Software Engineer role focused on building next-generation AI-powered platforms at Visa. This involves designing and delivering scalable data, infrastructure, and agent-driven systems for intelligent decision-making, production-grade GenAI platforms, distributed data pipelines, and autonomous workflow systems. The role requires strong programming skills, DevOps/infrastructure experience, and specific experience with GenAI/LLM systems including training, fine-tuning, RAG, vector databases, and agentic AI platforms.

What you'd actually do

  1. Design code and systems that touch 40% of the world population while influencing Visa’s internal standards for scalability, security, and reusability
  2. Collaborate multi-functionally to create design artifacts and develop best-in-class software solutions for multiple Visa technical offerings
  3. Actively contribute to product quality improvements, valuable service technology, and new business flows in diverse agile squads
  4. Develop robust and scalable products intended for a myriad of customers including end-user merchants, b2b, and business to government solutions.
  5. Leverage innovative technologies to build the next generation of Payment Services, Transaction Platforms, Real-Time Payments, and Buy Now Pay Later Technology

Skills

Required

  • Python
  • Java
  • building scalable backend services
  • automation frameworks
  • DevOps
  • infrastructure engineering
  • containerization (Docker)
  • orchestration (Kubernetes)
  • CI/CD pipelines (GitHub Actions, Jenkins, Argo)
  • Infrastructure-as-Code (Terraform, Pulumi)
  • streaming platforms (Kafka, Flink, Pulsar)
  • deploying distributed systems at scale on cloud platforms (AWS, Google Cloud, or Microsoft Azure)
  • supporting GenAI and LLM-based systems
  • building pipelines for model training
  • fine-tuning
  • RAG workflows
  • managing embeddings
  • vector databases (Pinecone, Weaviate, FAISS, Milvus)
  • designing prompt retrieval and context management systems
  • developing agentic AI platforms using multi-agent architectures and orchestration frameworks (LangGraph, LangChain, AutoGen, MCP)
  • secure tool integration
  • API orchestration
  • observability for autonomous workflows
  • data observability
  • logging
  • monitoring
  • reliability frameworks for AI and data pipelines
  • collaborating with Data Scientists, ML Engineers, and AI platform teams to productionize GenAI applications
  • performance, reliability, and governance
  • one or more general development languages (e.g., Java, C#, C++)
  • building and deploying modern service

Nice to have

  • BI and visualization tools such as Tableau, Power BI, or Superset

What the JD emphasized

  • 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience
  • 3+ years of experience with strong DevOps and infrastructure engineering
  • 3+ years of experience supporting GenAI and LLM-based systems

Other signals

  • building production-grade GenAI platforms
  • distributed data pipelines
  • autonomous workflow systems
  • AI-first financial infrastructure