Job Description

🟢 At Dev.Pro, we work on projects that impact millions of people around the world — but we know it’s the people behind the tech who make it all happen. We truly value what makes each person unique and are building a workplace that’s inclusive, friendly, and supportive.

About this opportunity

We are looking for a DevOps Engineer to join our remote engineering team. The Cloud Data Platform Engineer will play a central role in the deployment, monitoring, and optimization of cloud platforms used by our data scientists. This role requires hands-on expertise in cloud infrastructure, modern DevOps practices, secure data operations, and automation frameworks. You’ll partner closely with data scientists, machine learning engineers, and data engineers to ensure our analytics systems run securely, efficiently, and at scale. You’ll work with our Platform Engineering team to define and implement these patterns so they can be codified and reused across our organization.

🧩 Key responsibilities and your contribution

• Cloud Infrastructure & Operations Manage, scale, and optimize cloud environments used for data science workloads (primarily AWS, Databricks, dbt). Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker). Implement and maintain high-availability solutions for mission-critical analytics platforms. Deep expertise in AWS resource management and provisioning, including IAM roles and permissions.
• DevOps & Automation Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing using industry standard toolchains. Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK). Automate provisioning, configuration, and deployments using tools such as Terraform and CloudFormation, GitHub actions, etc.
• Data Platform Support Enable and improve data ingestion, transformation, and model execution workflows through platform capabilities and automation. Develop and maintain self-service capabilities for data scientists to provision and manage reliable, reproducible environments for research and development. Collaborate with Data Engineering to maintain integrations between data pipelines and cloud systems. Share responsibility for provisioning and operating application networking capabilities that support data platforms, including API gateways, CDNs, application load balancers, TLS, and WAFs.
• Security, Compliance & Governance Implement and operationalize data science security and compliance controls for data science platforms in alignment with enterprise cloud standards. Conduct periodic risk assessments,best practice reviews, and remediation efforts to strengthen security and resiliency. Support secure handling of sensitive financial data.
• Cross-Functional Collaboration Partner with data scientists, machine learning engineers, and data engineers to deeply understand and support their needs and workflows within data-driven initiatives. Serve as a technical advisor on cloud architecture, performance optimization, and production readiness for data and ML platforms. Adopt and champion Agile, DevOps, and Platform Engineering practices (kanban, scrum, continuous improvement, automation, Everything-as-a-Service). Demonstrate a strong, proactive focus on serving internal customers, prioritizing user experience, identifying opportunities to leverage automation and self-service to reduce toil and cognitive load for developers and researchers.

✅ Is that you?

• A bachelor’s degree or higher in a STEM field, required
• 5+ years of experience in cloud operations, DevOps, platform engineering, SRE, sysadmin or related roles.
• Strong proficiency with at least one major cloud provider (AWS preferred).
• Hands-on experience with IaC tools (Terraform, CloudFormation, or similar).
• Strong scripting skills (Python, Bash, or PowerShell).
• Strong understanding of modern authentication and authorization technologies and secrets management (IAM, OIDC, OAuth2, RBAC, ABAC, privileged access management, JIT authorization, PKI).
• Experience with common CI/CD systems (GitHub Actions, Jenkins, GitLab CI, ArgoCD,, or similar).
• Familiarity with container orchestration (Docker Compose, EKS/Kubernetes, ECS).
• Experience supporting data-intensive or ML workloads.

✅ Nice to have

• Experience in financial services, investment management, or other highly regulated industries.
• Knowledge of ML/AI platform tools (Databricks, SageMaker, MLflow, Airflow).
• Hands-on experience with AI Engineering and LLMOps tools (LLM observability, eval pipelines, building/supporting agentic workflows) are a huge plus.
• Understanding of networking, VPC architectures, and cloud security best practices.
• Familiarity with distributed compute frameworks (Spark, Ray, Dask).

🎾 What's working at Dev.Pro like?

✔️ 30 paid days off each year — use them for vacation, holidays, or personal time
✔️ 5 paid sick days, up to 60 days of medical leave, and 6 paid days off for family events like weddings, funerals, or having a baby
✔️ Partially covered health insurance - after probation
✔️ Wellness bonus for gym memberships, sports nutrition, and similar needs

Our next steps:

✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Internal interview — ✅ Client interview — ✅ Offer

Interested? Find out more:

📋How we work

💻 LinkedIn Page

📈 Our website

💻IG Page