Senior DevOps Engineer

About SCALIS

SCALIS is building a modern Applicant Tracking System (ATS) and CRM platform that helps employers manage their entire hiring pipeline — from sourcing and job posting to candidate evaluation, interview scheduling, and offers. Our platform serves employers, job seekers, and recruiters with AI-powered features including candidate matching, sourcing agents, and intelligent automations.

About the Role

We're looking for a DevOps Engineer to own and evolve the infrastructure, CI/CD pipelines, and developer experience across the SCALIS platform. You'll work with a microservices architecture spanning 10\+ services, real-time data pipelines, and a GitOps-driven deployment model. This role is hands-on — you'll be writing Kubernetes manifests, tuning CI workflows, debugging production incidents, and making the lives of our product engineers dramatically better.

What You'll Do

• Own the CI/CD platform: Maintain and improve GitHub Actions workflows across 10\+ repositories (build, test, lint, deploy, migration, e2e). Optimize build times, reduce flakiness, and keep pipelines reliable.

• Manage Kubernetes infrastructure: Operate EKS clusters across development, staging, and production environments. Write and maintain Kustomize overlays, Helm charts, deployments, HPAs, PDBs, and ingress configurations.

• Drive GitOps deployments: Manage the ArgoCD-based deployment pipeline. Ensure image tag updates flow cleanly from CI through gitops-workloads to cluster sync, with automated rollback on failure.

• Operate the data pipeline: Maintain the Change Data Capture pipeline that keeps our search layer in sync. Monitor connector health, troubleshoot replication lag, and ensure data consistency.

• Manage databases: Oversee PostgreSQL on AWS RDS. Coordinate schema migration rollouts across environments, manage connection pooling, monitor query performance, and handle backup/restore procedures.

• Maintain message infrastructure: Operate Kafka-compatible event streaming clusters. Manage topics, consumer groups, and schema evolution across services.

• Improve observability: Expand Datadog integration for metrics, traces, and logs. Build dashboards, set up alerts, and establish SLOs for critical user paths.

• Secure the platform: Manage AWS IAM roles, secrets, TLS certificates, and network policies. Ensure least-privilege access across services.

• Improve developer experience: Maintain the Docker Compose-based local development environment (15\+ services), optimize build caches, and reduce friction for engineers running the full stack locally.

• Capacity plan and cost optimize: Right-size pod resources, manage reserved instances, and optimize ECR image storage and S3 costs.

What We're Looking For

Required:

• 4\+ years of experience in a DevOps, SRE, or Platform Engineering role

• Strong Kubernetes experience (EKS preferred) — you've written deployments, HPAs, PDBs, and ingress configs from scratch, not just applied Helm defaults

• GitHub Actions expertise — building reusable workflows, matrix strategies, self-hosted runners, caching, and artifact management

• AWS proficiency — EC2/EKS, RDS (PostgreSQL), S3, ECR, IAM, Secrets Manager, CloudWatch, and VPC networking

• Experience with GitOps tools, specifically ArgoCD and Kustomize

• Hands-on Docker experience — writing multi-stage Dockerfiles, optimizing image sizes, and debugging container networking

• Solid understanding of PostgreSQL operations — migrations, connection pooling, performance tuning, backup/recovery

• Experience with event streaming platforms — Kafka or similar (topic management, consumer group monitoring, connector operations)

• Comfortable with TypeScript/Node.js — enough to read application code, debug startup failures, and understand build tooling

• Infrastructure-as-Code experience — Terraform, CDKTF, Pulumi, or equivalent

Nice to Have:

• Experience with Debezium or other CDC tools

• OpenSearch/Elasticsearch operations (index management, cluster tuning, mapping configuration)

• Cloudflare or similar edge/CDN management

• Datadog or comparable observability platform experience

• Familiarity with third-party SaaS integration webhook infrastructure

• Redis operations for caching and job queue systems

• Experience scaling platforms from startup to growth stage (we're moving fast)

• KEDA or other event-driven autoscaling experience