Senior GenAI & Automation Platform Engineer

Visa

Ashburn (VA)

Hybrid

USD 111,000 - 172,000

Full time

9 days ago

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Job summary

Visa's Global Operations team seeks a GenAI Platform Engineer to help shape AI-driven operations for a world-scale payments platform. You will build reusable GenAI platforms, integrate LangGraph/LangChain, and apply AWS Bedrock/SageMaker to improve reliability and automation.

Collaborate with distributed teams, implement CI/CD, containerization, and observability, delivering secure, scalable AI solutions. Hybrid work model in the US with in-office days; Visa values innovation and continuous

Qualifications

2+ years of relevant work experience and a Bachelor’s degree, OR 5+ years of relevant work experience.
2-5 years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.
Experience working within Agile development environments, including SAFe and globally distributed teams
Technical Experience
Generative AI frameworks and tools such as LangGraph, LangChain, Haystack, AWS Bedrock, or similar platforms.
Backend development using Python, with FastAPI strongly preferred.
Frontend development using React and TypeScript.
Event-driven architectures and messaging technologies such as Kafka/MQ/SQS
Vector databases and retrieval technologies such as FAISS, Pinecone, Weaviate, OpenSearch, or similar solutions.
CI/CD automation and developer platforms, including GitHub, Bitbucket, Jira, Jenkins, ServiceNow, and related tooling.

Responsibilities

Design and build reusable GenAI platforms, SDKs, pipelines, and shared frameworks that accelerate AI adoption across engineering teams.
Develop solutions using agent frameworks such as LangGraph, LangChain, Haystack, or similar technologies.
Implement modern AI architectures leveraging AWS services including Bedrock, SageMaker, embeddings, vector databases, and agentic workflows.
Design and optimize Retrieval-Augmented Generation (RAG) architectures, LLM orchestration layers, evaluation frameworks, and LLMOps processes.
Design and develop production-ready AI applications using: Backend: Python, FastAPI, Flask, Node.js, Kafka; Frontend: React, TypeScript, and REST/GraphQL integrations.
Build secure APIs, microservices, event-driven architectures, and enterprise integrations.
Create intuitive, scalable user experiences for AI-powered products and platforms.
Implement CI/CD automation using tools such as GitHub Actions, Jenkins, Bitbucket, Jira, ServiceNow, and Artifactory.
Apply containerization, automated testing, infrastructure-as-code (Terraform, CloudFormation), and deployment best practices.
Ensure robust monitoring, logging, observability, and recovery strategies; collaborate with cybersecurity teams.