workday
Software Engineer - Sr.Consultant Level - Python, React, GenAI Architecture
Visa
Bengaluru, IND
Full-time
Senior · 11+ years experience
Discovered 2 weeks ago
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awsbedrockcloudformation
Role Overview
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.
Key Skills for This Role
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Qualifications
- Basic Qualifications:
- 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.
- 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.
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