Senior DevOps Engineer 3

Responsibilities:

• You take end-to-end ownership of infrastructure, design, scale, and operate it. This goes beyond execution. Here's what that looks like day to day:
• Own the design, architecture, and reliability of Locus's cloud infrastructure across AWS, Azure, GCP, and Aliyun, supporting multi-region, global deployments.
• Lead the evolution of our CI/CD ecosystem and optimize and refactor our Jenkins-as-Code setup for scalability, performance, and developer efficiency.
• Drive the Infrastructure as Code (IaC) journey end-to-end, migrating existing cloud resources, alarms, and configurations fully into code with strong versioning, review, and rollback practices.
• Partner with engineering teams to identify and resolve performance, scalability, and reliability bottlenecks; deep dives into memory, CPU, networking, and storage constraints.
• Define and implement monitoring, alerting, and incident response best practices; improve MTTR, system observability, and operational readiness.
• Lead initiatives around cost optimization, security hardening, and capacity planning and keep infrastructure efficient and compliant as the platform scales.
• Act as a technical mentor for junior DevOps engineers and raise the overall DevOps maturity across teams.

Requirements:

• 7+ years of experience as a DevOps / Platform Engineer in a SaaS or product-led company.
• Strong hands-on expertise in at least one major cloud provider (AWS / Azure / GCP) with exposure to multi-cloud or global deployments.
• Deep experience designing and operating CI/CD pipelines, preferably Jenkins, or equivalent tools like GitHub Actions and GitLab CI.
• Proven experience with Infrastructure as Code tools, Terraform, CloudFormation, or similar.
• Strong background in monitoring and observability, CloudWatch and similar tools, actionable alerting, and SLIs/SLOs.
• Strong analytical and debugging skills with the ability to reason about distributed systems and infrastructure trade-offs.
• Comfortable working cross-functionally, influencing design decisions, and operating in a high-ownership environment.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
• DevOps/SRE professional with ~[7+] years of experience in designing, building, and managing scalable cloud infrastructure and Kubernetes platforms.
• Strong expertise in CI/CD, Infrastructure as Code (Terraform), and observability, with a focus on reliability, performance, and cost optimization.

Strong Signals - We Actively Look for These:

• Degrees don't tell us much. These do:
• You've designed and operated infrastructure that spans multiple cloud providers and geographies.
• You've led a full IaC migration, from legacy click-ops to fully versioned, reviewed, and automated.
• You've measurably improved MTTR through better observability and incident response and you have the numbers.
• You've built something on your own time, an open-source side project, or an internal tool.
• You've contributed to a top open-source project.
• You've filed a patent or published research.
• You've written technical content others reference or spoken at a conference.
• You've competed in or completed something grueling: ultra-marathons, Ironmans, competitive programming, or hackathon wins.
• We don't fill seats. We hire builders who build for other builders.

The Stack:

• Cloud: AWS, Azure, GCP, Aliyun (multi-region, global) CI/CD: Jenkins-as-Code, GitHub Actions, GitLab CI IaC: Terraform, CloudFormation.
• Observability: CloudWatch, SLI/SLO frameworks, incident response tooling.
• Platform: Kubernetes, Kafka, PostgreSQL, Redis, and Elasticsearch Scale: 350+ deployments, 30+ countries, billions of deliveries, and high-volume daily computations.

Key Skills and Technical Expertise:

• Primary Skills: Kubernetes, Terraform, AWS/GCP, CI/CD (GitHub Actions/Jenkins), SRE practices.
• Secondary Skills: Networking, Security, Cost Optimization, and System Design.
• Tools/Technologies: Docker, Helm, Prometheus, Grafana, ArgoCD, Kafka, Redis.
• Domain Experience: Cloud Infrastructure, SaaS Platforms, and AI/ML workloads (GPU-based systems).