We are seeking a GenAI Architect / Sr Consultant, Software Engineer (L6.5) who is both a hands-on full-stack engineer and a team leader capable of designing, developing, and deploying GenAI‑powered applications. You will manage and 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. While building components of powerful payment technology, you will get to see your efforts shaping the digital future of monetary transactions.

Preferred Qualifications:

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD.

Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.

8+ years of software engineering experience; 2+ years leading or mentoring engineers.

Worked with Agile SDLC process and SAFE agile environment in distributed teams

Hands-on experience with:

LLM frameworks (LangGraph, LangChain, Haystack, AWS Bedrock GenAI tools)

Python backend development (FastAPI strongly preferred)

Frontend development (React + TypeScript)

Vector databases (FAISS, Pinecone, Weaviate, OpenSearch, etc.)

Agile Frameworks like SAFE, GitHub / Bitbucket, Jira, ServiceNow, Wiki, CI/CD automation pipelines involving Jenkins

Proven experience shipping products on AWS (Lambda, ECS/EKS, S3, API Gateway, Bedrock, SageMaker).

Strong understanding of distributed systems, microservices, and API design.

Experience implementing RAG at scale using internal or cloud-based vector stores.

Experience with Databricks/Spark pipelines, MLFlow, or modern MLOps tools.

Familiarity with event-driven messaging systems (Kafka, Kinesis).

Background in payments, risk, fraud analytics, or regulated financial systems.

Experience creating developer tooling or reusable frameworks for broader engineering teams.