Software Engineer III – Real-Time Payments

About the role

As a Software Engineer III in Real‑Time Payments Services you will design, build and operate mission‑critical payment platforms that process high‑throughput transactions. The role combines deep expertise in payment systems with modern cloud‑native, micro‑service and AI‑enabled operational practices.

Key responsibilities

• Lead production incident management for payment flows (P1/P2), including triage, war‑room coordination, mitigation, root‑cause analysis and preventive actions.
• Develop and scale microservices for payment initiation, validation, routing, settlement, reconciliation and exception handling.
• Implement distributed in‑memory data patterns using VMware GemFire / Apache Geode for ultra‑low‑latency caching.
• Build AI‑assisted observability use cases such as anomaly detection, alert correlation and incident prediction.
• Own release quality with CI/CD gates, canary/blue‑green strategies, rollback automation and zero‑downtime deployments.
• Collaborate with product, risk, compliance and partner banks to ensure secure, compliant payment outcomes.

Required profile

• Formal training or certification in software engineering and at least 3 years of applied experience.
• Bachelor’s degree in Computer Science, Cybersecurity, Data Science or related field.
• Strong Java ecosystem skills (Java 11+, Spring Boot) and experience with REST/gRPC APIs.
• Hands‑on experience with microservices architecture and domain‑driven service decomposition.
• Proficiency with VMware GemFire / Apache Geode (regions, partitioning, WAN replication, CQ/events).
• Extensive experience on AWS (EKS/ECS, EC2, VPC, ALB/NLB, S3, RDS/Aurora, ElastiCache, IAM, CloudWatch, KMS, Secrets Manager).
• Solid background in incident management for high‑availability systems, including on‑call duties and post‑incident remediation.
• Experience with messaging and streaming technologies such as Kafka, MQ, SNS/SQS.
• Knowledge of security and compliance requirements in financial systems (encryption, tokenization, audit controls).
• Demonstrated use of approved AI‑assisted development tools and understanding of responsible AI practices.

Required skills

• Java 11+, Spring Boot
• REST, gRPC
• Microservices, Domain‑Driven Design
• VMware GemFire / Apache Geode
• AWS (EKS, ECS, EC2, VPC, ALB/NLB, S3, RDS/Aurora, ElastiCache, IAM, CloudWatch, KMS, Secrets Manager)
• Kubernetes, Docker, containers
• Kafka, MQ, SNS, SQS
• Observability tools (Datadog, Splunk, ELK, Prometheus, Grafana, OpenTelemetry)
• CI/CD pipelines, Git
• AI‑assisted development tools (Microsoft Copilot, Claude)