Job Title: DevOps Engineer
Location: Austin, Texas
Type: Full Time
Our client is looking for a highly skilled DevOps Engineer to lead cloud infrastructure, CI/CD automation, and modern deployment architecture across containerized environments. If you enjoy building secure, scalable systems and collaborating with full‑stack engineering teams, this role offers the chance to influence DevOps strategy and drive technical excellence.
What You’ll Do
- Architect and maintain scalable CI/CD pipelines using cloud‑based DevSecOps platforms.
- Build and optimize Docker‑based microservices, images, and deployment workflows.
- Lead deployments across Docker Swarm, Kubernetes/EKS, and multi‑site environments.
- Develop automation for infrastructure provisioning using Terraform, Ansible, Bash, and Git‑driven workflows.
- Manage advanced release pipelines including registries, artifact feeds, templated pipelines, and multi‑stage deployments.
- Define deployment strategies across development, QA, staging, and production environments.
- Implement cloud‑native solutions on AWS and Azure.
- Apply secure access practices including IAM configuration, secrets management, and permissions governance.
- Build modular, reusable systems for repeatable builds and releases.
- Collaborate closely with teams working in Angular, Java, Python, backend APIs, and database engineering.
- Mentor junior DevOps engineers and contribute to long‑term DevOps roadmap planning.
Required Skills & Expertise
- Azure DevOps, YAML pipelines, Git branching strategies.
- Docker, Docker Compose, Docker Swarm, multi-location deployments.
- Azure infrastructure and AWS (IAM, Lambda, S3, CloudWatch).
- Python, Bash, Linux/Unix, shell tools, Groovy.
- Ansible playbooks, inventory design, configuration management.
- Multi-site replication, IP‑based node selection, dynamic routing.
- PostgreSQL, MySQL, MariaDB operations and migrations.
- Prometheus, Grafana, CloudWatch, metrics and observability.
- Git, submodules, registries, artifact storage, secrets management.
- Interest or experience in AI/ML technologies.
Education & Experience
- Bachelor’s degree in Computer Engineering, Computer Science, or related field (Master’s preferred).
- 7+ years of experience in DevOps, software engineering, or testing within enterprise software or infrastructure environments.
