Sr. Staff Software Development Engineer

The Opportunity Join Adobe as a Senior Staff Engineer and play a critical role in building and evolving the engineering platforms that power Adobe products such as Adobe Express. This role sits at the intersection of software engineering, site reliability engineering, and AI-powered platform innovation, with a focus on enabling safe, scalable, and efficient software delivery at enterprise scale. You will work on foundational systems that support multi-tenant, multi-region cloud services used by millions of customers worldwide. As a senior technical leader, you will drive reliability, automation, and AI-enabled engineering productivity, helping shape how Adobe builds, deploys, and operates modern software systems. What You’ll Do Design, build, and evolve highly reliable software systems and platforms that support large-scale, distributed services. Architect and implement AI-powered automation systems that enhance cloud infrastructure and software delivery workflows, including intelligent orchestration of LLMs, tools, APIs, and internal data sources. Configure and manage services running on Kubernetes-based platforms, partnering with platform teams on application configuration, deployment, and operational correctness. Lead the development of GitOps-based workflows, CI/CD systems, and deployment automation to improve consistency, safety, and velocity across engineering teams. Build and maintain infrastructure-as-code using tools such as Terraform to provision and manage cloud resources on AWS (e.g., CloudFront, S3, and related services). Apply SRE principles to the design and operation of software systems, emphasizing reliability, scalability, risk management, and operational efficiency through sound engineering practices and automation. Balance near-term engineering needs with longer-term platform investments, delivering incremental improvements with durable impact. What You Need to Succeed A degree in Computer Science, Engineering, or equivalent practical experience. 10 years of professional software engineering experience, including significant experience building and operating distributed, cloud-native systems at scale. Hands-on and extensive experience working with Kubernetes-based platforms. Strong understanding and practical use of LLMs and AI systems in production environments. Proven ability to design reliable, scalable, and secure AI-enabled production workflows that connect models, runtime constraints, and engineering use cases into cohesive architectures. Strong programming skills in one or more languages commonly used in platform engineering (e.g., Typescript, Go, Java, Python, or similar). Excellent cross-functional communication skills and the ability to influence architectural direction through technical leadership. Preferred Qualifications Experience architecting or contributing to AI assistants, copilots, or agentic platforms used in production environments. Hands-on experience designing agent-based systems, including multi-step reasoning workflows, tool invocation, memory persistence, and state management. Familiarity with tool-augmented LLM systems, retrieval-augmented generation (RAG) architectures, vector databases, and contextual memory stores. Contributions to open-source AI frameworks, technical publications, or internal AI platform initiatives. What Sets You Apart You have strong systems thinking, with the ability to connect distributed architectures, cloud infrastructure, and AI-enabled automation into cohesive, production-ready solutions. You adopt a pragmatic approach to AI integration, balancing innovation with reliability, security, governance, and operational discipline. You demonstrate the ability to design intelligent automation systems that measurably improve engineering productivity, delivery velocity, and operational stability. You have a deep understanding of production system behavior, including scalability limits, failure modes, observability patterns, and risk m ... (truncated, view full listing at source)