Curate, instrument, and document systems so AI copilots and autonomous runbooks can observe, learn, and act safely (telemetry, feature flags, guardrails).
Drive engineering excellence through thoughtful design reviews, automated testing, chaos/resilience practices, and codified reliability standards.
Improve developer experience with automated pipelines, infrastructure-as-code, policy-as-code, and AI-enabled tooling that shorten feedback loops.
Coach and mentor engineers on AI-first ways of working: prompt literacy, pair-programming with copilots, responsible-use guidelines, and experimentation discipline.
Balance transformation ambition with delivery commitments by making pragmatic, data-informed engineering trade-offs and communicating risks early.
Experience you’ll need to have
Proven experience delivering software in complex, distributed, highly regulated environments.
Expert-level Java skills plus fluency with modern frameworks, testing libraries, and build tooling.
Hands-on experience with AWS (or comparable cloud) and building cloud-native, containerised services on Kubernetes.
Working knowledge of event-driven architectures and streaming platforms such as Kafka; able to model, test, and operate event flows at scale.
Experience with CI/CD, infrastructure automation, observability stacks, and Site Reliability/DevOps practices.
Demonstrated use of AI-assisted engineering tools (e.g., GitHub Copilot, internal copilots) or building ML/LLM-enabled services; comfort applying AI responsibly.
Strong collaboration and communication skills with the ability to influence cross-functional partners and navigate enterprise governance.
Thank you for considering employment with Fiserv. Please
Apply using your legal name
Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).
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