AWS DevOps / MLOps Engineer

Capnexus is a comprehensive services provider. Our team consists of outstanding professionals, highly experienced in designing, building, and supporting retail software. We see ourselves as a build-as-a-service provider who follows a repeatable business pattern that can be applied to a variety of platforms and verticals. Having a culture built on outcomes and delivery at the core of the business, Capnexus is providing its customers with a complete suite of services for software development, system analysis, integration, implementation, and support, as well as the option to engage a single team to perform all the services they require.  

Who You Are and What You'll Do:  

Capnexus is looking for a highly motivated and experienced AWS DevOps / MLOps Engineer to join our growing team. This is an exciting opportunity for a driven professional passionate about building cutting-edge cloud, automation, and AI-enabled infrastructure solutions in enterprise AWS environments.

We are specifically looking for candidates with deep hands-on AWS DevOps experience, ideally including experience working with or alongside AWS Professional Services (AWS ProServe) teams.

Responsibilities:

• Collaborate with cross-functional engineering, infrastructure, and AI teams to design, implement, and maintain scalable AWS cloud environments and CI/CD pipelines.
• Build, automate, and manage AWS-based infrastructure supporting development, production, and AI/ML workloads.
• Design and maintain Infrastructure as Code (IaC) solutions using Terraform, AWS CDK, and CloudFormation.
• Develop and optimize CI/CD pipelines using Azure DevOps and GitHub Actions/GitHub CI/CD workflows.
• Support deployment, monitoring, automation, and operational excellence across cloud-native applications and services.
• Work closely with development and AI teams to integrate modern AI tooling and automation capabilities into engineering workflows.
• Implement best practices around reliability, scalability, observability, security, and performance optimization in AWS environments.
• Participate in architecture discussions, infrastructure planning, troubleshooting, and continuous improvement initiatives.
• Support MLOps-related workflows and infrastructure for AI-enabled applications and services.

Qualifications:

• Bachelor’s degree in Computer Science or a related field.
• Strong hands-on experience as an AWS DevOps Engineer or MLOps Engineer in enterprise environments.
• Experience working with or supporting AWS Professional Services (AWS ProServe) engagements is strongly preferred.
• Deep expertise with AWS services including Lambda, API Gateway, Step Functions, ECS/EKS, IAM, CloudWatch, Amplify, and other core AWS technologies.
• Expert-level experience with Terraform, AWS CDK, and CloudFormation.
• Strong experience building and maintaining CI/CD pipelines using:
  • Azure DevOps
  • GitHub Actions / GitHub CI/CD
• Experience incorporating AI-enabled development tooling and automation into engineering workflows.
• Familiarity with modern AI engineering tools such as Kiro CLI or similar AI-assisted development tooling.
• Strong scripting/programming skills in Python or similar languages.
• Experience with infrastructure monitoring, logging, and performance optimization.
• Experience with databases such as RDS, PostgreSQL, Oracle, and DynamoDB.
• Strong understanding of DevOps, cloud security, automation, and infrastructure best practices.
• Excellent troubleshooting, analytical, and problem-solving skills.
• Strong communication and collaboration abilities in cross-functional enterprise environments.
• Ability to work independently in fast-paced, highly technical client-facing environments.

Nice to Have:

• Experience supporting AI/ML infrastructure or MLOps workflows.
• Experience with Kubernetes, Docker, and container orchestration.
• Experience supporting front-end deployments and modern web applications (ReactJS or similar).
• AWS certifications (Solutions Architect, DevOps Engineer, Machine Learning Specialty, etc.).
• Experience with version control systems such as Git.

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