Software Engineer - Sr. Consultant Level

Visa Visa · Fintech · Bellevue, WA

Visa is seeking a Sr. Consultant Software Engineer to architect, design, and build scalable backend systems that integrate AI agents into Visa's enterprise infrastructure. The role involves integrating LLMs, building RAG pipelines, and developing agentic workflows using frameworks like LangChain. The engineer will also focus on scalability, reliability, and leadership within the AI platform development.

What you'd actually do

  1. Architect and evolve the Agentic AI Platform to support multi-agent orchestration, retrieval-augmented generation (RAG), and integration with existing Visa microservices.
  2. Integrate Large Language Models (LLMs) such as GPT, Claude, Mistral, and Gemini into backend systems.
  3. Lead the design and implementation of distributed, fault-tolerant systems that scale horizontally.
  4. Partner with other senior engineers, ML engineers, and product leads to define and deliver the platform roadmap.
  5. Explore new frameworks, architectures, and deployment models to push the boundaries of Agentic AI in production.

Skills

Required

  • Java (Spring Boot)
  • Python (FastAPI/Flask)
  • RESTful and gRPC APIs
  • Large Language Models (LLMs)
  • RAG pipelines
  • vector databases (Pinecone, Weaviate, FAISS)
  • LangChain, LangGraph, or Autogen
  • Kubernetes
  • Docker
  • Prometheus/Grafana
  • cloud platforms (AWS, GCP, Azure)
  • SQL and NoSQL databases
  • containerization and CI/CD pipelines

Nice to have

  • React front-end applications
  • Model Context Protocol (MCP) frameworks
  • event-driven architectures
  • message queues (Kafka, RabbitMQ)
  • MySQL
  • DynamoDB
  • MongoDB
  • ArgoCD
  • Jenkins
  • GitHub Actions

What the JD emphasized

  • Production-level experience in building and deploying AI Agentic solutions
  • Hands-on experience implementing LLM, GenAI, and RAG systems using frameworks such as LangChain, LangGraph, or Autogen.
  • Strong understanding of AI orchestration and LLM integration patterns in distributed environments.

Other signals

  • building scalable backend systems that integrate AI agents
  • architect, design, and build scalable backend systems
  • integrate Large Language Models (LLMs) such as GPT, Claude, Mistral, and Gemini into backend systems
  • Build and optimize RAG pipelines using vector databases
  • Develop orchestration and agentic workflows