Software Engineer, Sr. Consultant - Fullstack GenAI Enablement

About Visa

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.

Visa’s Technology Organization is a community of problem solvers and innovators reshaping the future of commerce. We operate the world’s most sophisticated processing networks capable of handling more than 65k secure transactions a second across 80M merchants, 15k Financial Institutions, and billions of everyday people. While working with us you’ll get to work on complex distributed systems and solve massive scale problems centered on new payment flows, business and data solutions, cyber security, and B2C platforms.

We are seeking a seasoned Fullstack Software Engineer with experience building GenAI-enabled applications. The role requires both hands‑on full‑stack engineering and leadership capabilities. You will mentor an engineering team while delivering scalable AI systems that integrate with Visa’s product ecosystem, developer platforms, and internal operational tools.

This role blends architecture, leadership, full‑stack development, cloud engineering, and GenAI frameworks. As a Visa Lead Engineer you will be an integral part of a multi‑functional development team inventing, designing, building, and testing software products that reach a truly global customer base.

• Ensure Visa’s diverse portfolio of commercial services performs optimally, meeting stringent availability targets and exceeding client expectations.
• Architect automation and GenAI into our operational DNA, embedding AIOps into our strategic foundation to innovate with intention.
• Design robust observability, intelligent event detection, and incident management for high‑throughput systems.
• Set operational standards to support both current and future business demands as technology evolves.
• Foster a blame‑free post‑mortem culture, encouraging curiosity and learning for team growth.

• Lang Graph, Lang Chain, Haystack, or similar agent frameworks
• AWS GenAI services (Bedrock, Sage Maker, “Strands”‑style agent pipelines, embeddings, vector stores)
• RAG architectures, custom LLM orchestration, model evaluation, LLMOps workflows
• Build reusable GenAI components, SDKs, pipelines, and abstraction layers for engineering teams.

• Prompt engineering and evaluation
• LLM safety, guardrails, and content filtering
• Embedding generation and vector database integrations
• Model lifecycle governance and deployment optimization
• Full‑stack engineering (hands‑on development)

• Backend:
  Python, FastAPI, Flask, Node.js
• Frontend:
  React + Type Script, UI component frameworks, REST/Graph
  
  QL integration
• Build secure APIs, microservices, event‑driven components, and backend integrations for AI systems.
• Design intuitive, responsive, production‑grade user interfaces for GenAI‑powered tools.
• Data pipelines & CI/CD engineering

• ETL/ELT pipelines
• Data preparation for LLM training/fine‑tuning
• Embedding pipelines and retrieval data stores

• Jenkins, Git Hub/Bitbucket, Jira, Wiki, Git Hub Actions, Code Pipeline, Artifactory or similar systems
• Automated testing, containerization, deployment, quality gates
• Infrastructure‑as‑code (Cloud Formation, Terraform)
• Ensure automated monitoring, logging, observability, and rollback strategies.
• Governance, security & responsible AI

• Model explainability
• Data governance and redaction
• Security boundaries, access control, encryption
• Responsible AI guidelines and compliance expectations
• Work with cybersecurity teams to…