Sr Software Engineer

Senior Software Engineer

Engineering • Bangalore, India (Hybrid) • Full-Time

Mission-Critical Core Banking Platform • Cloud-Native • Low-Latency Transaction Processing

About the Role

ACI Worldwide is seeking a Senior Software Engineer to join the team building and operating a mission-critical, low-latency core banking platform. Our product is architected cloud-natively and containerized from the ground up, deployed initially on Microsoft Azure / AKS with a clear roadmap to Red Hat OpenShift, AWS, and Google Cloud Infrastructure (GCI). Every design decision — from threading models to deployment topology — is made with high throughput, sub-millisecond latency, and five-nines availability in mind.

This is a full-stack engineering role in the deepest sense: you will design and build features end to end, own the reliability and performance of what you ship, actively contribute to the CI/CD pipeline and quality strategy, and provide L3 production support when the platform counts on it. We are also on an active modernization journey, migrating mission-critical COBOL logic to modern Java services, and your ability to read, understand, and translate legacy COBOL will be highly valued.

We are looking for self-motivated, driven engineers who take pride in craftsmanship, embrace AI as an accelerator across the full development lifecycle, and are genuinely excited to grow their careers at ACI Worldwide.

Location & Work Model

Location: Bangalore , India

Work Model: Hybrid — on-site on designated days; remote-eligible on other days per team and business needs

Key Responsibilities

1) Low-Latency Application Engineering

• Design, implement, and optimize high-performance Java services for real-time transaction processing: payments, authorization, clearing, and settlement workflows where latency and correctness are non-negotiable.

• Apply deep JVM knowledge — threading models, garbage collection tuning, lock-free data structures, and async I/O — to sustain predictable throughput under peak load.

• Define and enforce performance budgets: author benchmarks, regression tests, and latency SLOs; profile and root-cause regressions before they reach production.

• Build against modern cloud-native patterns: microservices, event-driven messaging (NATS), reactive pipelines, and 12-factor application design.

2) Cloud-Native & Container-First Development

• Write software that is container-native from day one: images must be lean, stateless where possible, and fully operable on Kubernetes (AKS, OpenShift, EKS, GKE).

• Collaborate with the DevOps/Platform team on Kubernetes manifests, Helm/Carvel packaging, resource requests/limits, health probes, and rolling deployment strategies.

• Understand and contribute to GitOps workflows; ensure application configuration is version-controlled, auditable, and environment-agnostic.

• Design for multi-cloud portability from the start: avoid cloud-vendor lock-in in application code and dependency choices.

3) AI-Augmented Development Lifecycle

• Leverage AI tools actively across the SDLC: AI-assisted code generation and review, test case synthesis, documentation drafting, defect analysis, and performance diagnostics.

• Apply responsible AI practices: validate all AI-generated output for correctness, security, and maintainability before merging; never place secrets, PII, or PCI data into AI prompts.

• Contribute to team-level AI adoption: share effective patterns, prompt strategies, and tooling discoveries that raise the velocity and quality bar for the whole team.

• Stay current with AI/ML advancements relevant to banking — intelligent anomaly detection, automated triage, fraud signal enrichment — and propose production-ready applications.

4) Quality Engineering & Test Automation

• Own quality for what you ship: write comprehensive unit, integration, and contract tests; enforce non-negotiable coverage thresholds and quality gates in CI.

• Author and maintain end-to-end test scenarios for transaction processing flows; partner with Quality Engineering to integrate Testkube-orchestrated test suites into the pipeline.

• Practice shift-left quality: treat a bug escaping to staging as a process failure, not an expected outcome.

• Participate in code reviews with a quality lens: correctness, edge cases, error handling, observability hooks, and long-term maintainability….