We are looking for a Staff Backend Engineer who is passionate about building platforms at scale, loves challenging engineering problems, and enjoys empowering other engineers to move faster with confidence.
As a member of Cloudinary’s Backend Platform Team, you will own and evolve the backend platform: core shared services (for example, service mesh, shared locking, multi-tenant fairness and rate-limiting), the tooling and processes behind our Software Development Lifecycle (CI/CD pipelines, development environments, release workflows), and AI-powered operational tooling for production visibility and incident response. You’ll work closely with DevOps, Architecture and Product engineering teams to turn these needs into reliable, scalable, and reusable platform capabilities.
Responsibilities
Design, build, and own core platform services that support Cloudinary’s backend services at scale (e.g., service mesh, shared locking, fairness and rate-limiting, and other shared infrastructure components).
Lead end-to-end engineering initiatives - from discovery and architecture, through implementation and rollout, to observability and ongoing operations.
Improve developer experience and productivity, evolving development environments, Blueprint projects, and frameworks that streamline service creation (e.g., Go services, AWS Lambda).
Drive the evolution of our AI-powered operational tooling and agents, helping design, build, and maintain systems that analyze, evaluate, and assist in resolving production and on-call issues.
Advance deployment and operational excellence, driving improvements in reliability, performance, and safety of our deployment and release lifecycle.
Provide technical leadership and mentorship, influencing platform strategy and engineering best practices across teams and partnering closely with DevOps and product engineering.
Technical skills & experience
10+ years of experience in backend or platform engineering, including designing and building production systems at scale.
Strong hands-on experience with Golang, or significant experience with another backend language with a strong desire and ability to ramp up on Go.
Experience working with AWS and cloud-native architectures, including services such as EC2, S3, SQS, Kinesis, EKS, Lambda, Aurora, and core concepts like IAM, VPC, networking, and autoscaling.
Proven experience designing and operating systems at scale - thinking about high availability, multi-tenancy, throughput, latency, cost, and graceful degradation rather than just correctness in small environments.
Practical experience with Docker and containerized workloads.
Experience with distributed systems and service-to-service communication (e.g., service meshes, RPC, concurrency, resiliency patterns).
Experience with monitoring and observability tools, such as Kibana, Coralogix, Datadog, CloudWatch, CloudTrail, Rollbar, Athena, or similar.
Proven technical leadership: driving complex projects, making architectural decisions, and aligning stakeholders across teams.
Comfortable both designing and building services from scratch and working productively in large, existing codebases.
Soft skills & ways of working
Great team player and communicator - easy to collaborate with, able to explain complex technical topics clearly to different audiences.
Autodidact and curious, not shy about asking questions to fully understand ideas, requirements, and systems.
Able to actively engage with other teams, understand their workflows and pain points, and translate them into practical platform solutions.
Open-minded and collaborative, able to consider and accept other people’s ideas, even when they contradict your own.
Growth mindset - driven to learn and improve rather than assume you already know it all.
Comfortable mentoring and guiding other engineers, giving constructive feedback and helping raise the bar for engineering quality.
Embraces the use of AI tools and workflows in day-to-day work, looking for ways to leverage AI to increase productivity, quality, and operational excellence rather than resisting it.
Nice to have
Experience with at least two of Ruby, Node.js or Python and their relevant web frameworks in production systems.
Experience with Kubernetes and container orchestration.
Experience with ArgoCD or other GitOps deployment tools.
Background in building internal developer platforms or shared infrastructure for other teams.
Experience designing or integrating AI/LLM-powered operational tools or agents (for observability, incident response, or developer productivity).
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