Senior Cloud Development Engineer, Cloud Backing Services

Cloud Backing Services builds and evolves the foundational cloud services used across Pega Cloud. Our team focuses on the engineering behind these services: defining supported architectures and configurations, automating provisioning, improving self-service capabilities, and helping teams use cloud backing services safely and efficiently at scale. 

For Kafka, we provide platform engineering expertise that makes the service consistent, scalable, secure, observable, and appropriate for different workload patterns. We partner closely with Cloud Operations, application engineering, security, and infrastructure teams. Routine day-to-day production operations are owned by a dedicated operations team; Cloud Backing Services becomes directly involved when a case requires deeper platform expertise, non-standard analysis, or a systemic engineering improvement. 

We are a globally distributed engineering team that values ownership, curiosity, pragmatic problem solving, automation, knowledge sharing, and continuous improvement. 

You will be one of the engineers shaping how Kafka is delivered and consumed across Pega Cloud. You will work on problems that sit at the intersection of distributed systems, cloud infrastructure, automation, performance, reliability, and cost - from choosing the right service patterns and sizing guidance to investigating difficult behaviors that cannot be solved through standard operational procedures. 

You will turn recurring problems into durable engineering solutions: better provisioning, clearer guardrails, stronger diagnostics, improved documentation, and safer platform capabilities. You will also use modern AI-assisted engineering tools as a practical multiplier for investigation, analysis, automation, prototyping, documentation, and knowledge discovery - while applying sound engineering judgement and validating the results. 

• Design and evolve Kafka-based cloud capabilities offered to engineering teams.
• Partner with application teams on architecture, sizing, rightsizing, capacity planning, partitioning, storage, retention, replication, and expected workload growth.
• Perform root-cause analysis and turn difficult or recurring cases into improvements in automation, diagnostics, platform standards, and documentation.
• Use AI-assisted engineering tools to accelerate log and configuration analysis, hypothesis exploration, code and automation development, documentation, and prototyping - and critically validate generated output.
• Identify opportunities to apply AI and automation to reduce repetitive work, shorten feedback loops, improve developer experience, and increase engineering leverage.
• Collaborate with cloud infrastructure, security, platform, and application engineering teams on cross-cutting technical challenges and architectural decisions.
• Share knowledge, mentor other engineers, and help raise engineering standards across Cloud Backing Services. 

• You are a systems thinker who enjoys understanding how distributed components interact and where failures, bottlenecks, or hidden constraints can emerge.
• You take ownership of ambiguous technical problems and can drive them from investigation through design, implementation, and measurable improvement.
• You collaborate effectively across engineering and operations, communicate clearly, and can explain complex technical trade-offs to different audiences.
• You are not constrained by organizational hierarchy. When faced with a task, you proactively engage with anyone who can provide relevant context - regardless of their role or seniority - to understand different use cases and identify the best path forward for everyone involved.
• You are pragmatic: you balance reliability, scalability, performance, complexity, security, and cost rather than optimizing a single dimension in isolation.
• You naturally look for ways to replace repetitive manual work with automation, self-service capabilities, better tooling, or clearer platform patterns.
• You are curious about new technologies - including AI-assisted engineering - and know how to experiment quickly while keeping engineering judgement, validation, security, and accountability with the human engineer. 

• Strong hands-on experience with Apache Kafka in large-scale environments.
• Solid understanding of Kafka architecture and behavior, including brokers/controllers, topics, partitions, replication, consumer groups, shared groups, offsets, rebalancing, retention, and failure modes.
• Experience diagnosing complex problems in Kafka or other distributed systems and identifying underlying technical causes.
• Experience with at least one major public cloud platform, preferably AWS or Google Cloud.
• Experience with Infrastructure as Code and automated platform delivery, such as Terraform and CI/CD or GitOps workflows.
• Experience using Go, Python, Java, or another programming/scripting language to build automation, tooling, or platform capabilities.
• Good understanding of cloud networking, DNS, TLS, identity and access management, and observability concepts relevant to distributed services.
• Professional experience working with cross-functional engineering teams and communicating effectively in English.