Senior Software Engineer – Product Reliability Engineering (Middleware) at 110 Visa U.S.A. Inc.

Language

Setup: Hybrid
Location: Singapore
Type: Full-time
Level: mid
Posted: Jun 2, 2026

Description

Visa is hiring a Software Engineer for its Middleware Product Reliability Engineering team in Singapore. The role focuses on building production-grade automation, deployment orchestration, observability, troubleshooting, and agentic AI platforms that improve the reliability and availability of Visa's global middleware. Engineers will write Python, Java, or Go, use DevOps and cloud tools, and contribute to monitoring, self-healing systems, and AI-driven reliability workflows. The position is hybrid, with the expected number of office days to be confirmed by the hiring manager.

Required Skills

Python
Java
Go
LangChain
LangGraph
Kubernetes
Terraform
Prometheus
Grafana
Kafka
Flink

Additional Information

Minimum Education: Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
Required Previous Experiences: 2+ years of relevant work experience with a bachelor's degree, or 5+ years of relevant work experience.
3–5 years of professional software engineering experience, or equivalent SRE/DevOps experience with strong coding skills.
Hands-on experience with Jenkins, Terraform, Ansible, Docker, and Kubernetes.
Familiarity with AWS, GCP, or Azure.
Working knowledge of monitoring and observability tools.
Comfort with Linux/Unix environments and command-line fluency.
Preferred Qualifications: 3+ years of work experience with a bachelor's degree, or more than 2 years with an advanced degree.
Proficiency in Python, Java, or Go for production-quality code.
Foundations in data structures, algorithms, and systems design.
Curiosity about generative AI and agentic systems.
Middleware experience with Tomcat, Apache, Spring Boot, JBoss, IBM MQ, IBM DataPower, Hazelcast, Kafka, Flink, or SQS.
AI/ML engineering experience or hands-on work with LLM frameworks and RAG pipelines.
Experience integrating AI agents or LLMs into production systems.
Experience with event-driven and streaming architectures.
Networking fundamentals including DNS, load balancing, service mesh, and TCP/IP.
Open-source contributions or a public engineering portfolio.