Talent Space
We're looking for a skilled
Cloud DevOps Engineer
with a strong background in cloud infrastructure, automation, and DevOps for a contract to hire opportuntiy in Thousand Oaks, CA!
What You'll Do:
Design, implement, and manage scalable, reliable infrastructure in
AWS
to support high-availability systems. Build and maintain
Windows and Linux server environments , ensuring seamless integration across hybrid and cloud platforms. Use
Infrastructure as Code (IaC)
tools like
AWS CloudFormation, CDK, Terraform, and OpenTofu
to automate infrastructure provisioning and configuration. Implement
configuration management
using
Chef
to maintain consistency across Windows and Linux systems. Design and optimize
CI/CD pipelines
using
GitLab CI/CD , supporting automated deployment workflows for
.NET applications . Integrate
generative AI services
such as
AWS Bedrock ,
Google Agentspace , and similar tools into the platform to support scalable and secure AI delivery. Develop infrastructure to support large-scale
AI/ML pipelines
for model training, inference, and deployment across
AWS and GCP
environments. Automate the full AI/ML model lifecycle-training, deployment, monitoring-ensuring reproducibility and smooth collaboration between data science and engineering teams. Partner with AI engineers to deliver reusable APIs, scalable infrastructure, and tools that accelerate innovation and adoption of machine learning across the organization. Implement robust
observability ,
cost management , and
security/privacy
strategies tailored to AI workloads, including resource-efficient scaling and monitoring of inference services. Ensure
infrastructure and deployment security
aligns with best practices and compliance standards. Collaborate with software engineering teams to understand their needs and provide
DevOps solutions
that improve velocity and reliability. Troubleshoot and resolve infrastructure or deployment issues across environments. Deploy and manage
monitoring and logging systems
to ensure real-time visibility and proactive issue detection. Contribute to the creation and documentation of internal
DevOps best practices , standards, and tooling. Stay current with evolving trends in
cloud infrastructure, DevOps automation, and AI platform engineering . Offer
mentorship and support to junior team members , helping grow the team's technical capabilities.
Qualifications:
Qualifications: Bachelor's degree in
Computer Science ,
Engineering , or a related field - or equivalent practical experience. 5+ years of professional experience
in a
DevOps
or
Site Reliability Engineering (SRE)
role, with a strong track record of supporting production systems. At least
1 year of experience working with AI services and large language models (LLMs) , including integration and orchestration. Extensive hands-on experience with
Amazon Web Services (AWS)
and cloud-native architectures. Solid knowledge of both
Windows and Linux server administration , including experience integrating these environments within cloud platforms. Proven expertise with
Infrastructure as Code (IaC)
tools, particularly
AWS CDK
and
Terraform . Strong experience building and managing
CI/CD pipelines , especially using
GitLab CI/CD . Experience deploying and maintaining
.NET applications
in cloud environments. Deep understanding of
cloud security best practices
and how to implement them across infrastructure and CI/CD workflows. Solid grasp of
networking fundamentals , including
TCP/IP ,
DNS ,
load balancing , and
firewall configuration
in cloud-based systems. Hands-on experience with
monitoring and logging tools
such as
New Relic ,
AWS CloudWatch , or similar platforms. Strong scripting skills in languages such as
PowerShell ,
Python ,
Ruby , or
Bash . Excellent
problem-solving abilities
and the capacity to troubleshoot complex systems efficiently. Strong
communication and collaboration skills , with the ability to work effectively across teams and departments. Experience with
containerization technologies
like
Docker
and
Kubernetes
is a plus. AWS and/or GCP certifications
are a strong advantage. Familiarity with
Chef
for configuration management is preferred.
Cloud DevOps Engineer
with a strong background in cloud infrastructure, automation, and DevOps for a contract to hire opportuntiy in Thousand Oaks, CA!
What You'll Do:
Design, implement, and manage scalable, reliable infrastructure in
AWS
to support high-availability systems. Build and maintain
Windows and Linux server environments , ensuring seamless integration across hybrid and cloud platforms. Use
Infrastructure as Code (IaC)
tools like
AWS CloudFormation, CDK, Terraform, and OpenTofu
to automate infrastructure provisioning and configuration. Implement
configuration management
using
Chef
to maintain consistency across Windows and Linux systems. Design and optimize
CI/CD pipelines
using
GitLab CI/CD , supporting automated deployment workflows for
.NET applications . Integrate
generative AI services
such as
AWS Bedrock ,
Google Agentspace , and similar tools into the platform to support scalable and secure AI delivery. Develop infrastructure to support large-scale
AI/ML pipelines
for model training, inference, and deployment across
AWS and GCP
environments. Automate the full AI/ML model lifecycle-training, deployment, monitoring-ensuring reproducibility and smooth collaboration between data science and engineering teams. Partner with AI engineers to deliver reusable APIs, scalable infrastructure, and tools that accelerate innovation and adoption of machine learning across the organization. Implement robust
observability ,
cost management , and
security/privacy
strategies tailored to AI workloads, including resource-efficient scaling and monitoring of inference services. Ensure
infrastructure and deployment security
aligns with best practices and compliance standards. Collaborate with software engineering teams to understand their needs and provide
DevOps solutions
that improve velocity and reliability. Troubleshoot and resolve infrastructure or deployment issues across environments. Deploy and manage
monitoring and logging systems
to ensure real-time visibility and proactive issue detection. Contribute to the creation and documentation of internal
DevOps best practices , standards, and tooling. Stay current with evolving trends in
cloud infrastructure, DevOps automation, and AI platform engineering . Offer
mentorship and support to junior team members , helping grow the team's technical capabilities.
Qualifications:
Qualifications: Bachelor's degree in
Computer Science ,
Engineering , or a related field - or equivalent practical experience. 5+ years of professional experience
in a
DevOps
or
Site Reliability Engineering (SRE)
role, with a strong track record of supporting production systems. At least
1 year of experience working with AI services and large language models (LLMs) , including integration and orchestration. Extensive hands-on experience with
Amazon Web Services (AWS)
and cloud-native architectures. Solid knowledge of both
Windows and Linux server administration , including experience integrating these environments within cloud platforms. Proven expertise with
Infrastructure as Code (IaC)
tools, particularly
AWS CDK
and
Terraform . Strong experience building and managing
CI/CD pipelines , especially using
GitLab CI/CD . Experience deploying and maintaining
.NET applications
in cloud environments. Deep understanding of
cloud security best practices
and how to implement them across infrastructure and CI/CD workflows. Solid grasp of
networking fundamentals , including
TCP/IP ,
DNS ,
load balancing , and
firewall configuration
in cloud-based systems. Hands-on experience with
monitoring and logging tools
such as
New Relic ,
AWS CloudWatch , or similar platforms. Strong scripting skills in languages such as
PowerShell ,
Python ,
Ruby , or
Bash . Excellent
problem-solving abilities
and the capacity to troubleshoot complex systems efficiently. Strong
communication and collaboration skills , with the ability to work effectively across teams and departments. Experience with
containerization technologies
like
Docker
and
Kubernetes
is a plus. AWS and/or GCP certifications
are a strong advantage. Familiarity with
Chef
for configuration management is preferred.