BI Enterprise Systems Engineer V (DevOps) Bitovi · Remote · Worldwide · DevOps & Release In listing 2mo ago

Devopsroles; United States; Hybrid; USD 120,000 - 180,000; Full time

Job summary

Avalara is seeking a mid-to-senior DevOps Engineer to own the AI workflow infrastructure (including n8n) in a remote, full-time capacity. You will lead the design, deployment, and operation of secure, observable platforms that support AI-driven automations across tax and finance workflows.

You will champion reliability, governance, and cross-team collaboration, mentoring engineers and citizen developers while advancing AI-enabled operations.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
• 5+ years in DevOps, SRE or platform engineering with ownership of production systems.
• Experience with a major cloud provider and container orchestration, plus hands-on IaC.
• Ownership of CI/CD pipelines and production monitoring, including security checks, service targets and alerts.
• Experience supporting shared platforms used by multiple teams and applying AI in engineering or operations with clear results.

Responsibilities

• Own environments, pipelines, containers, clusters, storage, secrets and network services behind AI workflow tools.
• Build security and privacy controls into platform setup and deployment pipelines.
• Set reliability targets and production monitoring, improving MTTR and change failure rates.
• Provide reusable templates, IaC modules and deployment patterns for consistency across teams.
• Coach engineers and citizen developers, applying AI to improve platform operations and delivery.

Skills

Cloud provider experience

Container orchestration

CI/CD ownership

Infrastructure as Code

Production monitoring

AI in engineering

Education

Bachelor's or Master's in CS/Engineering

Tools

Terraform

Job description

Mid-level DevOps & Release role at Bitovi. Remote · full-time.

devopsroles summary, based on the employer's posting.

What you'll do

• Own the environments, delivery pipelines, containers, clusters, storage, secrets and network services behind n8n and related workflow tools
• Build security and privacy controls into platform setup, including hardened configurations, access boundaries and safeguards in deployment pipelines
• Set reliability targets and production monitoring, then use incident lessons to lower recovery times and failed changes
• Provide reusable templates, infrastructure modules and deployment patterns so teams can build workflows consistently
• Coach engineers and citizen developers, and apply AI tools to improve platform operations and delivery

What you bring

• A bachelor's or master's degree in computer science, engineering or a related discipline
• At least five years in DevOps, SRE or platform engineering, with direct responsibility for production systems
• Strong experience with a major cloud provider and container orchestration, plus hands‑on infrastructure-as-code work
• Experience owning CI/CD pipelines and production monitoring, including security checks, service targets and alerts
• You have supported shared platforms used by multiple teams and applied AI in engineering or operations with clear results

Who this fits

This is a senior, hands‑on platform role suited to someone who can own production infrastructure while raising engineering practices across teams. The work centers on secure, observable AI workflow services, including n8n, and mentoring both engineers and citizen developers. The role is listed as remote.

From the employer

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 DevOps 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 DevOps 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/DevOps 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.

We are hiring a DevOps 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 DevOps workflows in ways that 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 DevOps 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.
• 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 partner with architecture, security, and platform teams to align AI workflow infra with Avalara's Software Maturity Model and engineering governance, moving the platform and guiding teams to higher levels of maturity.
• Bar Raiser for DevOps & AI‑First Ways of Working
• You elevate how teams build and operate automations by mentoring engineers, codifying best practices, and using AI tools yourself to materially improve speed, quality, and reliability of the AI workflow platform.

12‑Month Success Signals

Within 12 months, you will have demonstrably:

• Stood up an Enterprise‑Grade AI Workflow Platform
• n8n and at least one additional AI workflow tool are running on a governed, multi‑environment platform (dev/test/prod) with standardized CI/CD, IaC, and security controls in place.
• Improved Reliability and Change Management for AI Workflows
• Measurable reductions in incident frequency and MTTR for AI workflow infrastructure, along with reduced deployment failures or rollbacks for n8n‑backed automations.
• Raised Maturity and Governance Compliance
• Documented uplift in SMM/DevOps maturity scores for the AI workflow platform along CI/CD, security, IaC, and observability dimensions, with evidence used in audits and ARB reviews.
• Accelerated AI Workflow Delivery
• Multiple teams actively building on the platform using standardized patterns and templates, with data showing shorter time‑to‑production and reduced manual operations for AI workflow changes.
• Demonstrated Bar Raiser Impact
• Peer and leadership feedback, plus concrete examples, show you have raised standards for DevOps, automation, citizen developer adoption, and AI usage (e.g., documented patterns, training sessions, or platform improvements that others now rely on).

What You’ll Need To Be Successful

Avalara is an AI‑first company; this role must show applied AI impact, not casual tool usage. As a Senior DevOps Engineer for AI workflows, you are expected to leverage deep DevOps and platform engineering expertise to integrate AI into the software delivery and operations lifecycle in meaningful, measurable ways. This role should elevate how teams use AI across automation, observability, reliability, and release engineering, delivering tangible improvements in speed, stability, scalability, and operational excellence.

A successful candidate will

• Design AI‑Enhanced Operations for the Platform
• Use 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.
• Accelerate Infra and Automation Delivery with AI
• Apply 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.
• Embed AI into the Platform Experience Itself
• Partner 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.
• Share 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.

Qualifications

To be successful in this role, you must have:

• Education & Experience
  • 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.
• Core Technical Expertise
  • 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