Job Title: Senior DevOps Engineer
Location: Austin, Texas
Type: Full Time
Our client is looking for a Senior DevOps Engineer to architect and maintain modern DevSecOps environments across AWS and Azure—while mentoring engineers and shaping the DevOps roadmap.
This is a high‑impact role for someone who loves automation, cloud engineering, and modern deployment infrastructure.
What You’ll Do
- Architect and manage highly scalable CI/CD pipelines across Azure and AWS.
- Build and optimize Docker‑based microservices, images, and deployment pipelines.
- Lead deployments across Docker Swarm, Kubernetes, and EKS environments.
- Automate infrastructure using Ansible, Terraform, Bash, and Git‑based workflows.
- Manage release pipelines using artifact feeds, registries, and templated multi‑stage pipelines.
- Design environment strategies across dev, QA, staging, and production.
- Implement and integrate cloud‑native services across AWS and Azure.
- Apply security best practices (IAM roles, secrets management, access controls).
- Build secure, scalable, reusable build‑and‑release systems.
- Collaborate closely with full‑stack developers (Angular, Java, Python), backend API teams, and database engineers.
- Mentor junior DevOps engineers and contribute to long‑term DevOps strategy.
What You Bring
DevOps & CI/CD
- Azure DevOps pipelines, YAML templates, Git workflows, CI/CD architecture.
Containers & Orchestration
- Docker, Docker Compose, Docker Swarm, and multi‑node deployments.
Cloud Expertise
- Azure infrastructure
- AWS IAM, Lambda, S3, CloudWatch
Scripting & Automation
- Python, Bash, Linux/Unix automation, awk, groovy.
Infrastructure as Code
- Ansible (playbooks, roles, inventories)
- Terraform and configuration management
Distributed Deployments
- Multi‑site replication, node routing, dynamic service discovery.
Database Experience
- PostgreSQL, MySQL, MariaDB operations & migrations.
Monitoring & Observability
- Prometheus, Grafana, CloudWatch, logging & metrics pipelines.
Version Control & Release Management
- Git, Azure DevOps, artifact storage, container registries, secrets management.
Bonus
- Interest or experience in AI/ML engineering workflows.
Education & Experience
- Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or similar.
- Master’s degree preferred.
- 7+ years in DevOps, software engineering, or test engineering for enterprise‑scale systems (servers, networking, storage, etc.).
