Sr. DevOps Engineer
- WorkNovas LLC
2 Days Ago
NA
NA
Austin-TX
10-13 Years
Required Skills: EC2, ECS or EKS, Lambda, API Gateway, RDS, DynamoDB, Cloudwatch, S3, Github Actions, Code/Build/Pipeline/Deploy
Job Description
Role: Sr. DevOps Engineer
13+ years of experience
Location: Austin, Texas
Duration: 12+ Months Contract
Hybrid 3 days onsite
What You'll Do:
Infrastructure Design and Maintenance:
Design, improve, and maintain secure, durable, and performant infrastructure to power APIs, web applications, and data mining/ETL workflows to meet established SLAs.
Collaborate with developers to bring new products and services into production.
Automation and Monitoring:
Automate testing, deployment, and monitoring of all products and services throughout the software development lifecycle.
Continuously improve operational processes and apply best practices to ensure scalability, security, and availability.
Security and Compliance:
Proactively meet standards for information security and compliance, such as SOC 2/ISO27001.
Implement and uphold security measures across all infrastructure components.
Requirements:
Professional Experience:
At least 12 years of professional experience in a DevOps role maintaining production infrastructure, preferably supporting a highly available environment for a SaaS or cloud service provider.
Technical Proficiency:
Strong working knowledge of AWS services such as EC2, ECS or EKS, Lambda, API Gateway, RDS, DynamoDB, Cloudwatch, S3, Github Actions, Code/Build/Pipeline/Deploy, etc.
Strong working knowledge of Terraform or similar tools, Ansible, AWS CLI/SDK, Boto.
Proficiency with scripting languages such as Python, Bash, etc., and Linux environments.
Strong understanding of system and networking concepts and troubleshooting techniques for bare metal and containerized workloads.
Additional Skills:
Experience with release automation, system administration and configuration, and system debugging.
Nice to Have
Experience supporting AI and ML systems
Agent orchestration frameworks (e.g., AgentCore or similar).
Experience integrating LLMs into production systems.
Databricks and/or Snowflake infrastructure experience.
Cost optimization for AI and LLM workloads.
Internal developer platform experience.
