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Enterprise System Engineer V; DevOps

Job in Durham, Durham County, North Carolina, 27703, USA
Listing for: Bitovi
Full Time position
Listed on 2026-07-24
Job specializations:
  • IT/Tech
    SRE/Site Reliability, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 126000 - 244000 USD Yearly USD 126000.00 244000.00 YEAR
Job Description & How to Apply Below
Position: Enterprise System Engineer V (DevOps)

PLEASE NOTE:

Bitovi has been engaged by Avalara to lead initial and technical interviews for this role. While Bitovi will conduct the early rounds, the final interview and hiring decision will be made by Avalara directly.

What You'll Do Avalara is scaling an AI‑first automation ecosystem where tools like n8n and other AI workflow platforms orchestrate critical business processes across tax, finance, operations, and internal productivity. To do this safely and at scale, we need a Dev Ops leader who will design, set up, deploy, and run the underlying infrastructure and all components around it—including governance, security, observability, and reliability—for these AI workflow tools.

This Enterprise Systems Engineer, playing a senior Dev Ops Engineer role, exists to build a secure, enterprise‑grade AI workflow platform that teams can trust for high‑impact automations, reducing manual work, shortening cycle times, and improving uptime for AI‑powered workflows across Avalara.

How This Role Elevates Avalara

  • For teams:
    You provide a hardened, self‑service platform for AI workflows (starting with n8n) so product, operations, and IT teams can ship automations faster without reinventing infra or bypassing governance.
  • For the business:
    You increase operational reliability and speed by making AI workflows easy to change, safe to deploy, observable in production, and secure by design, directly improving SMM/Dev Ops maturity and audit readiness.
  • For customers:
    By stabilizing and scaling AI‑driven internal and product workflows, you reduce incidents, improve response times, and enable smarter, more automated experiences across Avalara's tax compliance platform.

Bar Raiser Expectations

We are hiring a Dev Ops Bar Raiser — someone who raises the performance, standards, and platform maturity of the teams they work with. This role is expected to improve how systems are architected, automated, deployed, and operated by enhancing engineering judgment, operational excellence, and cross‑functional delivery. As part of an AI‑first company, this role must also demonstrate applied AI impact by embedding AI into Dev Ops workflows to measurably improve speed, reliability, scalability, and overall engineering effectiveness.

  • Track record of raising standards for reliability, security, or automation through documentation, mentoring, or governance—leaving systems and processes stronger than you found them.
  • Ability to communicate clearly with engineering, security, operations, and business stakeholders, explaining trade‑offs and setting realistic expectations in non‑jargon language.
  • Experience with mentoring and providing support for citizen developers who are new to agentic AI and automation concepts.

If you are excited about building and running secure, AI‑ready workflow infrastructure and acting as a Bar Raiser for Dev Ops and AI at Avalara, we'd love to meet you.

What Your Responsibilities Will Be

In this role, you will own the end‑to‑end lifecycle of Avalara's AI workflow infrastructure, with clear accountability for outcomes rather than task lists:

  • Platform Ownership – AI Workflow Infra (incl. n8n):
    You are the technical owner for the infrastructure and core components that run n8n and related AI workflow tools—environments, CI/CD, containers, runtime clusters, storage, secrets, networking, and integrations—ensuring they are resilient, scalable, and cost‑effective.
  • Secure‑by‑Design Governance
    :
    You embed security, privacy, and compliance into how AI workflows are built and run: hardened baselines, secret management, network and IAM boundaries, and CI/CD guards that prevent unsafe changes from reaching production.
  • Operational Reliability & Observability
    :
    You define and drive SLOs, metrics, logging, and alerting for the AI workflow platform, turning incidents into systematic improvements that reduce MTTR and change failure rates over time.
  • Standardization & Reuse for AI Workflows
    :
    You create and enforce reusable patterns (templates, reference pipelines, IaC modules, guardrails) so teams building on n8n and other tools follow consistent, auditable practices instead of bespoke one‑offs.
  • Maturity & Governance Alignment (SMM / ARB):
    You…
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