About You
Are you a seasoned DevOps Engineer with a passion for AI and machine learning Do you thrive on empowering engineering teams with innovative AI/ML capabilities
If you answered YES then this is the perfect role for you!
Your Responsibilities
As our new DevOps (AI Exposure) you will work closely with DevOps and Software engineers to make sure all our systems are running smoothly and quickly respond to issues as they arise. Your strong engineering mindset and problem-solving skills will be essential in maintaining high system performance and stability. This role involves designing and implementing cloud-native and cloud-agnostic solutions that support both new initiatives and ongoing projects across the organization. This is a hybrid role two days a week in the office is required. Moreover you will:
- Build and maintain CI/CD pipelines optimized for AI/ML workflows.
- Manage containerization and orchestration using Docker and Kubernetes.
- Implement observability and monitoring for distributed AI agents.
- Ensure security scalability and cost-efficiency across AWS and Azure environments.
- Evaluate LLM-based tools to enhance engineering productivity.
- Define and promote engineering-wide AI standards and best practices.
- Collaborate across teams to drive AI adoption throughout the organization.
- Design and build solutions that integrate seamlessly with existing workflows and tooling.
Qualifications :
You Offer
- 4 years of experience in Platform Engineering or DevOps.
- Hands-on experience with AWS and Azure including tools like Amazon SageMaker and Bedrock.
- Proficiency with container technologies (Docker Kubernetes).
- Proven experience deploying GenAI or LLM-powered applications (1 year).
- Strong communication skills and a collaborative mindset in a remote-first environment.
- Passion for solving developer pain points and improving workflows.
- Ability to quickly learn and apply new technologies in a fast-paced setting.
- Familiarity with AI model evaluation metrics and data requirements.
Additional Information :
Please note that we will only consider candidates with a valid work permit.
Remote Work :
No
Employment Type :
Full-time
About YouAre you a seasoned DevOps Engineer with a passion for AI and machine learning Do you thrive on empowering engineering teams with innovative AI/ML capabilitiesIf you answered YES then this is the perfect role for you!Your ResponsibilitiesAs our new DevOps (AI Exposure) you will work closely ...
About You
Are you a seasoned DevOps Engineer with a passion for AI and machine learning Do you thrive on empowering engineering teams with innovative AI/ML capabilities
If you answered YES then this is the perfect role for you!
Your Responsibilities
As our new DevOps (AI Exposure) you will work closely with DevOps and Software engineers to make sure all our systems are running smoothly and quickly respond to issues as they arise. Your strong engineering mindset and problem-solving skills will be essential in maintaining high system performance and stability. This role involves designing and implementing cloud-native and cloud-agnostic solutions that support both new initiatives and ongoing projects across the organization. This is a hybrid role two days a week in the office is required. Moreover you will:
- Build and maintain CI/CD pipelines optimized for AI/ML workflows.
- Manage containerization and orchestration using Docker and Kubernetes.
- Implement observability and monitoring for distributed AI agents.
- Ensure security scalability and cost-efficiency across AWS and Azure environments.
- Evaluate LLM-based tools to enhance engineering productivity.
- Define and promote engineering-wide AI standards and best practices.
- Collaborate across teams to drive AI adoption throughout the organization.
- Design and build solutions that integrate seamlessly with existing workflows and tooling.
Qualifications :
You Offer
- 4 years of experience in Platform Engineering or DevOps.
- Hands-on experience with AWS and Azure including tools like Amazon SageMaker and Bedrock.
- Proficiency with container technologies (Docker Kubernetes).
- Proven experience deploying GenAI or LLM-powered applications (1 year).
- Strong communication skills and a collaborative mindset in a remote-first environment.
- Passion for solving developer pain points and improving workflows.
- Ability to quickly learn and apply new technologies in a fast-paced setting.
- Familiarity with AI model evaluation metrics and data requirements.
Additional Information :
Please note that we will only consider candidates with a valid work permit.
Remote Work :
No
Employment Type :
Full-time
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