Enterprise System Engineer V (DevOps)
$126,000–$201,600 year
On-siteDurham, North Carolina, United States
Job Summary
Own the end-to-end lifecycle of Avalara's AI workflow infrastructure, including environments, CI/CD, containers, and runtime clusters for tools like n8n. Embed security, privacy, and compliance into how workflows are built and run through hardened baselines, secret management, and CI/CD guards. Define and drive SLOs, metrics, logging, and alerting to reduce MTTR and change failure rates while standardizing reusable patterns and IaC modules. Partner with architecture and security teams to align the platform with the Software Maturity Model, mentoring engineers and citizen developers to elevate DevOps standards and AI usage across teams.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 5–8+ years in DevOps, SRE, or platform engineering for SaaS or large‑scale distributed systems, with direct ownership of production environments
- Strong experience with at least one major cloud provider (AWS, Azure, or GCP), including VPC design, security groups, load balancers, and managed Kubernetes (EKS/AKS/GKE) or equivalent container orchestration
- Deep hands‑on use of Infrastructure as Code (Terraform or equivalent) to manage multi‑environment infra and platform services
- Proven ownership of CI/CD pipelines (GitLab CI/CD or similar), including automated testing, security scanning, and artifact management for complex services or platforms
- Solid understanding of Linux and/or Windows, networking fundamentals (DNS, TLS, routing, firewalls), and secure secret management practices
- Hands‑on experience with logging and monitoring stacks (e.g., Sumo Logic, Splunk, Prometheus, Grafana, or equivalents) and defining meaningful SLOs and alerts for production systems
- Demonstrated experience running or supporting multi‑tenant or shared platforms used by multiple teams (internal developer platforms, workflow/orchestration tools, or integration platforms)
- Evidence of using AI tools in day‑to‑day engineering or operations (not just experimentation) with clear impact on speed, reliability, or quality
Desired Qualifications
- Experience with mentoring and providing support for citizen developers who are new to agentic AI and automation concepts
- Ability to communicate clearly with engineering, security, operations, and business stakeholders, explaining trade‑offs and setting realistic expectations in non‑jargon language
- Track record of raising standards for reliability, security, or automation through documentation, mentoring, or governance—leaving systems and processes stronger than you found them
- Experience using AI to augment incident triage, anomaly detection, capacity forecasting, and change‑risk assessment for n8n and related infra—e.g., AI‑assisted log analysis, pattern detection in pipeline failures, and recommendation of remediation steps
- Experience applying AI tools to speed up design and implementation of IaC, automated CI/CD pipelines, security policies, and runbooks, while still exercising strong judgment and governance over generated artifacts
- Experience partnering with integration and platform teams to enable AI‑driven orchestration patterns (for example, intelligent routing, adaptive retries, intelligent throttling) within n8n or surrounding services, where it meaningfully improves reliability or cost
- Experience sharing AI practices, patterns, and guardrails with engineers and citizen developers using the platform so AI materially improves outcomes (cycle time, incident reduction, automation coverage) instead of becoming ad‑hoc experimentation
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