Position: DevOps/MLOps Engineer
Location: Cumming GA
Duration: Long-term contract
Note: Final interview will take place onsite-only local candidates will be considered
Job Description:
- Our Fintech client is looking for an experienced DevOps / MLOps Engineer to help build and manage cloud infrastructure deployment pipelines and operational systems supporting AI-driven platform initiatives. This is a high-visibility role in a fast-moving environment where candidates are expected to make an immediate impact.
- Responsibilities:
- Develop implement and maintain CI/CD pipelines using tools such as GitHub Actions Jenkins or similar platforms
- Provision and manage cloud infrastructure across AWS Azure or GCP using infrastructure-as-code tools like Terraform or CloudFormation
- Support containerized environments and orchestration using Docker and Kubernetes
- Monitor system performance respond to incidents and help define and track service reliability metrics (SLOs/SLAs)
- Partner with engineering teams to streamline and improve deployment processes
- Apply security best practices including identity and access management secrets handling and network security policies
- Participate in on-call support as required
Qualifications:
- 7 years of experience in DevOps Site Reliability Engineering or platform engineering roles
- Strong hands-on experience with AWS
- Practical experience working with Kubernetes environments (EKS GKE or AKS)
- Proficiency with IaC tools such as Terraform
- Solid understanding of CI/CD methodologies and GitOps practices
- Experience with monitoring and observability tools such as Datadog Grafana or Prometheus
- Strong scripting ability in languages like Bash Python or TypeScript
- 1 years of experience supporting AI/ML infrastructure including GPU-based workloads or model deployment
- Familiarity with monorepo build systems such as Nx or similar tools
- Exposure to LLM integrations or AI platform ecosystems
- AWS certifications (e.g. Solutions Architect or DevOps Engineer
Position: DevOps/MLOps Engineer Location: Cumming GA Duration: Long-term contract Note: Final interview will take place onsite-only local candidates will be considered Job Description: Our Fintech client is looking for an experienced DevOps / MLOps Engineer to help build and manage cloud inf...
Position: DevOps/MLOps Engineer
Location: Cumming GA
Duration: Long-term contract
Note: Final interview will take place onsite-only local candidates will be considered
Job Description:
- Our Fintech client is looking for an experienced DevOps / MLOps Engineer to help build and manage cloud infrastructure deployment pipelines and operational systems supporting AI-driven platform initiatives. This is a high-visibility role in a fast-moving environment where candidates are expected to make an immediate impact.
- Responsibilities:
- Develop implement and maintain CI/CD pipelines using tools such as GitHub Actions Jenkins or similar platforms
- Provision and manage cloud infrastructure across AWS Azure or GCP using infrastructure-as-code tools like Terraform or CloudFormation
- Support containerized environments and orchestration using Docker and Kubernetes
- Monitor system performance respond to incidents and help define and track service reliability metrics (SLOs/SLAs)
- Partner with engineering teams to streamline and improve deployment processes
- Apply security best practices including identity and access management secrets handling and network security policies
- Participate in on-call support as required
Qualifications:
- 7 years of experience in DevOps Site Reliability Engineering or platform engineering roles
- Strong hands-on experience with AWS
- Practical experience working with Kubernetes environments (EKS GKE or AKS)
- Proficiency with IaC tools such as Terraform
- Solid understanding of CI/CD methodologies and GitOps practices
- Experience with monitoring and observability tools such as Datadog Grafana or Prometheus
- Strong scripting ability in languages like Bash Python or TypeScript
- 1 years of experience supporting AI/ML infrastructure including GPU-based workloads or model deployment
- Familiarity with monorepo build systems such as Nx or similar tools
- Exposure to LLM integrations or AI platform ecosystems
- AWS certifications (e.g. Solutions Architect or DevOps Engineer
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