Software Engineer, Sr. Consultant - Fullstack GenAI Enablement
Visa Inc.Ashburn, VA · full time · Senior
$152,200 – $243,700
Listed on Visa Inc.’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This is a senior full-stack engineering role focused on building and architecting GenAI-powered applications within Visa's global operations infrastructure, requiring both hands-on development and team leadership. The position suits experienced engineers comfortable across backend, frontend, and AI systems who can mentor others while delivering scalable AI solutions integrated into payment processing platforms.
Our summary, not Visa Inc.’s wording. The full posting is on their site.
Skills this role names
- Apache Kafka
- Artifactory
- AWS CloudFormation
- AWS CodePipeline
- AWS Lambda
- AWS SageMaker
- Bitbucket
- Databricks
- FastAPI
- Flask
- GitHub
- GitHub Actions
- GraphQL
- Jenkins
- Jira
- LangChain
- LangGraph
- Microservices
- MLflow
- Node.js
- Pinecone
- Python
- React
- REST APIs
- Retrieval-Augmented Generation (RAG)
- ServiceNow
- SPARK
- Terraform
- TypeScript
- Vector Databases
- Weaviate
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What they ask for
Required
- 8+ years relevant work experience (or 5+ with advanced degree, or 2+ with PhD)
- Full-stack software engineering across backend, frontend, and AI systems
- GenAI application architecture and development
- Experience with LLM frameworks such as LangGraph, LangChain, or Haystack
- Python backend development
- Frontend development with React and TypeScript
- Vector database implementation
- CI/CD pipeline automation
- AWS cloud platform proficiency
- Microservices and distributed systems understanding
- API design and implementation
Nice to have
- 9+ years relevant work experience (or 7+ with advanced degree, or 3+ with PhD)
- Bachelor's or Master's in Computer Science, Engineering, AI/ML, or related field
- 2+ years leading or mentoring engineers
- Agile and SAFe methodology experience
- Experience with Databricks, Spark, or MLFlow
- RAG implementation at scale
- Event-driven messaging systems (Kafka, Kinesis)
- Background in payments, risk, fraud analytics, or regulated financial systems
- Developer tooling or reusable framework creation