Software Development Engineer

Adobe Adobe · Enterprise · Bucharest, Romania

Software Development Engineer on the Adobe Experience Manager (AEM) Release Management team. This role focuses on building and owning production-critical systems for the entire AEM release lifecycle, leveraging AI-assisted capabilities for automation, analysis, and decision support in a large-scale, cloud-native enterprise environment. The core expectation is practical, production-grade AI fluency applied with judgment and safeguards.

What you'd actually do

  1. Design, build, and own systems supporting the end‑to‑end AEM release cycle, large‑scale, cloud‑native.
  2. Build release‑critical services, pipelines, tooling across the AEM release lifecycle, improve readiness, stability, and risk by aggregating signals from validation, testing, incidents, rollouts, reduce manual decisions through automation and AI‑assisted analysis, contribute to release platform architecture with product engineering, SRE, operations, build systems that scale across environments and regions with traceability, auditability, governance, own delivery end‑to‑end including CI/CD pipelines, monitoring, alerting, operational readiness, incident response, challenge non‑scaling practices and propose data‑backed improvements.
  3. Use AI‑assisted capabilities as part of the engineering platform, integrate AI‑based analysis and decision support into release systems, understand limitations and failure modes, design safeguards, fallbacks, human‑in‑the‑loop controls, ensure traceability, observability, accountability, evaluate AI behaviour over time including correctness, regressions, unintended effects.
  4. Systems‑oriented engineer, reliability‑first, automation‑driven, ownership mindset.

Skills

Required

  • Java
  • Python
  • Jenkins
  • Kubernetes
  • cloud-native platforms
  • automation
  • AI-assisted operational systems
  • enterprise environments
  • governance
  • object-oriented design
  • functional design
  • version control
  • full lifecycle ownership

Nice to have

  • REST
  • GraphQL
  • Grafana
  • Prometheus
  • infrastructure as code
  • environment automation
  • observability

What the JD emphasized

  • entire release lifecycle
  • platform capability
  • production-critical systems
  • AI fluency is a core expectation
  • AI fluency
  • production-grade AI fluency
  • AI-assisted analysis
  • AI workflows
  • AI behavior

Other signals

  • AI-assisted systems
  • production-critical systems
  • enterprise scale
  • AI fluency is a core expectation
  • AI is part of normal engineering practice
  • AI-based analysis and decision support
  • AI workflows