JoinedUp by Beeline is a modern SaaS platform for high-volume shift-based workforce management. We connect staffing suppliers, venues, and frontline workers with real-time booking, compliance, scheduling, and analytics. As part of the global Beeline ecosystem, we are expanding our AI capabilities to deliver smarter matching, predictive staffing, automated communications, and intelligent recommendations.
Purpose of the Position
We’re looking for a Mid-Level DevOps / Systems Engineer who is excited about both traditional infrastructure and emerging AI/ML platforms. You will report to our Engineering Manager and help build and operate the reliable, scalable AWS foundation that powers our core platform and our growing AI features (using Amazon Bedrock, Anthropic Claude, and similar tools).
This is a hands‑on role with room to grow: you’ll own meaningful projects, collaborate closely with backend and data teams, and help shape how we productionise AI workloads.
Responsibilities
Provision, and maintain scalable infrastructure on AWS using Terraform.
Deploy and manage containerised applications with Docker, Kubernetes, and AWS Fargate.
Write automation scripts and tools in Python and Bash.
Build and optimise CI/CD pipelines for both backend services and AI components using GitHub Actions.
Integrate and operate AI/ML services: Amazon Bedrock (model invocation, agents, knowledge bases, guardrails).
Monitor performance, cost, and reliability of both traditional and AI workloads (CloudWatch, Prometheus, custom dashboards).
Ensure security, compliance, and responsible AI practices (data privacy, model safety, cost controls).
Troubleshoot production issues and contribute to on‑call rotation.
Collaborate on infrastructure improvements that support AI‑driven features (e.g., real‑time shift recommendations, chat assistants, predictive no‑show detection).
Requirements (Skills and experience)
Essential Requirements (Mid‑Level)
3–5 years of hands‑on DevOps / Systems Engineering experience.
Solid experience with AWS core services (EC2, Fargate, VPC, IAM, S3, RDS, CloudWatch).
Working knowledge of Terraform (or similar IaC).
Proficiency with Docker and container orchestration (Kubernetes or ECS).
Comfortable scripting in Python and Bash.
Understanding of AI/ML operational concerns: latency, cost optimisation, model versioning, prompt engineering basics, and guardrails.
Good grasp of networking, security, and observability best practices.
Strong problem‑solving skills and eagerness to learn.
Nice‑to‑Have
Experience with CI/CD tools (GitHub Actions, CodePipeline, ArgoCD).
Exposure to real‑time or high‑volume SaaS systems.
Basic knowledge of data pipelines or event‑driven architecture (EventBridge, SQS, Kafka).
Practical experience integrating Amazon Bedrock and/or Anthropic Claude.
Equal Opportunity Employer Minorities/Women/Veterans/Disabled
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