Senior Software Developer – AI‑First Payment Services

About the role

Fiserv is reimagining payment technology through an AI‑first transformation. As a Senior Software Developer you will combine deep engineering expertise with AI‑assisted delivery to create the next generation of event‑driven, cloud‑native payment services that power millions of daily transactions worldwide.

Key responsibilities

• Design, build and ship high‑quality microservices and event‑driven capabilities for modern payment experiences.
• Partner with architecture, product, data‑science and AI platform teams to embed machine‑learning and AI‑assisted workflows.
• Lead the decomposition and modernization of legacy components using domain‑driven design, strangler patterns and AI‑accelerated refactoring.
• Instrument systems with telemetry, feature flags and guardrails so AI copilots and autonomous runbooks can operate safely.
• Drive engineering excellence through design reviews, automated testing, chaos‑engineering and codified reliability standards.
• Improve developer experience with automated pipelines, infrastructure‑as‑code, policy‑as‑code and AI‑enabled tooling.
• Coach engineers on AI‑first practices, prompt literacy and responsible use of AI tools.
• Balance transformation ambition with delivery commitments by making data‑informed trade‑offs and communicating risks early.

Required profile

• Proven experience delivering software in complex, distributed, highly regulated environments.
• Strong collaboration and communication skills with the ability to influence cross‑functional partners.
• Comfort applying AI responsibly and mentoring teams in AI‑first ways of working.

Required skills

• Expert‑level Java and modern Java frameworks.
• Hands‑on experience with AWS or comparable cloud platforms.
• Building cloud‑native, containerised services on Kubernetes.
• Event‑driven architectures and streaming platforms such as Kafka.
• CI/CD pipelines, infrastructure automation and observability stacks.
• Site Reliability Engineering / DevOps practices.
• Use of AI‑assisted engineering tools (e.g., GitHub Copilot) and building ML/LLM‑enabled services.