Job Overview
The pace of innovation in artificial intelligence and machine learning continues to accelerate, and the Data and Devices Business Unit is at the center of this transformation. Our customers are building intelligent systems that redefine how data is processed, analyzed, and used across compute, networking, and cloud infrastructure. At TE Connectivity, we support this evolution by delivering scalable, high-quality software solutions that enable next-generation products.
This role is a strong fit for someone with a solid software engineering and infrastructure foundation who is passionate about building reliable development platforms and automated deployment systems. You will work closely with software engineers, data scientists, machine learning engineers, and IT teams to build and maintain the infrastructure required to develop, deploy, and operate modern software and AI solutions at scale.
Job Responsibilities
As a DevOps Engineer, you will design, build, and maintain infrastructure and automation systems that support software development, machine learning workflows, and production deployments. You will help implement CI/CD pipelines, manage cloud infrastructure, and ensure systems operate reliably and securely in production environments.
You will also play a key role in enabling development teams to move quickly by automating workflows, improving deployment processes, and ensuring infrastructure scalability and reliability.
Key Responsibilities
Infrastructure and Platform Engineering
Design, build, and maintain scalable infrastructure to support software and machine learning applications.
Develop and manage cloud environments and compute resources used for development, testing, and production workloads.
Implement infrastructure as code practices to enable reproducible and automated infrastructure deployment.
Ensure systems are designed for high availability, scalability, and operational resilience.
Design, build, and maintain scalable infrastructure to support software and machine learning applications.
Develop and manage cloud environments and compute resources used for development, testing, and production workloads.
Implement infrastructure as code practices to enable reproducible and automated infrastructure deployment.
Ensure systems are designed for high availability, scalability, and operational resilience.
CI/CD and Automation
Design and maintain continuous integration and continuous deployment pipelines that automate build, testing, and deployment processes.
Implement automation tools that improve development productivity and reduce manual operational tasks.
Support version control workflows and automated testing processes across engineering teams.
Design and maintain continuous integration and continuous deployment pipelines that automate build, testing, and deployment processes.
Implement automation tools that improve development productivity and reduce manual operational tasks.
Support version control workflows and automated testing processes across engineering teams.
Containerization and Cloud Platforms
Build and manage containerized environments using technologies such as Docker and Kubernetes.
Deploy and maintain applications and services across cloud platforms such as AWS, Azure, or Google Cloud.
Optimize infrastructure and deployment pipelines to support scalable workloads and distributed systems.
Build and manage containerized environments using technologies such as Docker and Kubernetes.
Deploy and maintain applications and services across cloud platforms such as AWS, Azure, or Google Cloud.
Optimize infrastructure and deployment pipelines to support scalable workloads and distributed systems.
Monitoring and Reliability
Implement monitoring, logging, and alerting systems that ensure reliability of deployed services.
Track system performance and identify potential reliability or scalability issues.
Support incident response and root cause analysis for production system issues.
Implement monitoring, logging, and alerting systems that ensure reliability of deployed services.
Track system performance and identify potential reliability or scalability issues.
Support incident response and root cause analysis for production system issues.
Security and Compliance
Ensure infrastructure and deployment systems follow security best practices.
Implement secure configuration management and access control policies.
Support compliance with enterprise IT and cybersecurity standards.
Ensure infrastructure and deployment systems follow security best practices.
Implement secure configuration management and access control policies.
Support compliance with enterprise IT and cybersecurity standards.
Collaboration and Enablement
Work closely with software engineers, ML engineers, and data scientists to support deployment of applications and machine learning models.
Provide guidance on DevOps best practices, automation strategies, and infrastructure design.
Collaborate with cross functional teams to improve system reliability and development workflows.
Work closely with software engineers, ML engineers, and data scientists to support deployment of applications and machine learning models.
Provide guidance on DevOps best practices, automation strategies, and infrastructure design.
Collaborate with cross functional teams to improve system reliability and development workflows.
Required Skills & Competency
Bachelors with 5+ years, Masters with 3+ years, or PhD with 0+ years of experience in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
Strong programming and scripting skills in languages such as Python, Bash, or Go.
Experience building and maintaining CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, or similar platforms.
Experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.
Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
Experience with Infrastructure as Code tools such as Terraform, CloudFormation, or similar technologies.
Strong understanding of Linux systems, networking, and distributed system architectures.
Experience implementing monitoring and logging systems such as Prometheus, Grafana, ELK stack, or similar tools.
Strong analytical and problem-solving skills.
Ability to collaborate effectively with cross-functional engineering teams.
Clear communicator who works well in a collaborative team environment.
Self-motivated and eager to learn new technologies and continuously improve operational systems.
Ability to travel occasionally, up to 10%, for team meetings or training as needed.
Strong programming and scripting skills in languages such as Python, Bash, or Go.
Experience building and maintaining CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, or similar platforms.
Experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.
Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
Experience with Infrastructure as Code tools such as Terraform, CloudFormation, or similar technologies.
Strong understanding of Linux systems, networking, and distributed system architectures.
Experience implementing monitoring and logging systems such as Prometheus, Grafana, ELK stack, or similar tools.
Strong analytical and problem-solving skills.
Ability to collaborate effectively with cross-functional engineering teams.
Clear communicator who works well in a collaborative team environment.
Self-motivated and eager to learn new technologies and continuously improve operational systems.
Ability to travel occasionally, up to 10%, for team meetings or training as needed.
Competencies
Values: Integrity, Accountability, Inclusion, Innovation, Teamwork