Software Engineer III, Real-Time Payments Services

As a Software Engineer III in Real-Time Payments Services, you will build and run mission-critical Real-Time Payments (RTP) services with strong ownership across engineering, resiliency, release readiness, and incident response. The role requires deep experience in high-throughput payment systems and modern engineering capabilities across GemFire, AI-enabled operations, microservices, cloud-native architecture, and AWS. Job Responsibilities • Lead production incident management for payment flows (P1/P2), including triage, war-room coordination, mitigation, RCA, 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 state, reference data, and session/context caching. • Build AI-assisted observability and operations use cases (anomaly detection, alert correlation, incident prediction, runbook automation, GenAI-assisted triage). • Own release quality with CI/CD gates, canary/blue-green strategies, rollback automation, and zero/low-downtime deployments. • Collaborate with product, operations, risk, compliance, and partner banks/processors to deliver secure and compliant payment outcomes. • Ensure strong controls for audit/regulatory needs, data lineage, traceability, and operational reporting. • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 3+ years applied experience • Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or related disciplines • Strong Java ecosystem skills (Java 11+/Spring Boot), REST/gRPC APIs, asynchronous/event-driven design. • Proven experience with **microservices architecture** and domain-driven service decomposition. • Hands-on experience with **GemFire/Geode** (regions, partitioning, WAN replication, CQ/events, consistency/performance tuning). • Strong AWS experience: EKS/ECS, EC2, VPC, ALB/NLB, S3, RDS/Aurora, ElastiCache, IAM, CloudWatch, KMS, Secrets Manager. • Experience with cloud-native operations: containers, Kubernetes, autoscaling, health checks, service mesh (preferred). • Solid incident management background in high-availability systems, including on-call, runbooks, SRE practices, and post-incident remediation. • Messaging and streaming experience (Kafka, MQ, SNS/SQS) and resilient integration patterns. • Strong understanding of security and compliance in financial systems (encryption, tokenization, least privilege, audit controls). • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices Preferred qualifications, capabilities, and skills • Backend engineering; expeirence in payment platforms (RTP/instant payments preferred). • Microsoft Copilot and claude integration and analsys for L3 day 2 day work. • Observability stack experience (Datadog/Splunk/ELK, Prometheus/Grafana, OpenTelemetry, distributed tracing).