Senior Cloud Development Engineer, Cloud Backing Services

Pegasystems; Massachusetts; On-site; USD 102,000 - 153,000; Full time

Job summary

Pega is seeking a Kafka Platform Engineer to shape how Kafka is delivered across Pega Cloud. You will tackle distributed systems, cloud infrastructure, automation, performance, reliability, and cost—turning recurring problems into durable platform solutions with AI-assisted tooling, while applying sound engineering judgment and maintaining security.

You will collaborate with cloud infrastructure, security, platform, and application engineering teams, mentor engineers, and help raise engineering

Qualifications

• Hands-on Kafka in large-scale environments.
• Experience with at least one major public cloud (AWS or Google Cloud).
• Experience with Infrastructure as Code and automated platform delivery (Terraform, CI/CD or GitOps).
• Experience using Go, Python, Java for automation.

Responsibilities

• 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 workload growth.
• Perform root-cause analysis and turn difficult or recurring cases into automation and platform improvements.
• Use AI-assisted engineering tools to accelerate log/config analysis, hypothesis exploration, code and automation development, and documentation.
• Identify opportunities to apply AI and automation to reduce repetitive work and improve developer experience.

Skills

Kafka

Distributed systems

AWS

GCP

Terraform

CI/CD

GitOps

Go

Python

Java

Observability

English communication

Tools

Terraform

CI/CD

GitOps

Job description

Meet Our Team

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.

Meet Our Team

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.

Picture Yourself At Pega

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.

What You'll Do At Pega

• 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.

Who You Are

• 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.

What You've Accomplished

• 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.

Pega Offers You

• Gartner Analyst acclaimed technology leadership across our categories of products
• Continuous learning and development opportunities
• An innovative, inclusive, agile, flexible, and fun work environment
• Competitive global benefits program inclusive ofpay + bonus incentive, employee equity in the company

Additional Information

Base salary range for this role is 102,400 - 153,200 USD annually. This role may also be eligible for annual bonus OR commission, as well as benefits and other incentives.

The final compensation will be determined during the offer process based on the candidate's education, experience, skills, and qualifications, as well as market conditions and may vary from the posted range. We will share an information on benefits, bonus/commission, and other pay components for this role at the relevant recruitment stage.