Staff DevOps Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 44d ago
The date the source published, not the day we noticed it (2026-08-27). Last seen at its source 2h ago.
We have tracked this listing since 5 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Canada
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay CA$156.6k–198.8k/yr
Middle 50% of 193 listings that do state pay — Engineering · Senior · Canada · CAD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Ashby employer's own board first seen 5d ago · last seen 2h ago
The listing
Nexxa is building the best AI systems for heavy industries — enabling machines, systems, and operations to think, decide, and act autonomously across manufacturing, large-scale infrastructure, logistics, and legacy environments.
Our mission is to translate deep technical breakthroughs into operational reality, solving some of the hardest systems-level problems in industry.
About the Role
We're looking for a Senior/Staff DevOps Engineer who has spent the last several years building and operating the infrastructure that lets AI and industrial systems run reliably at scale. You understand what it takes to keep production ML and data workloads fast, observable, and resilient — from GPU-backed training and inference clusters to the pipelines that connect them to real-world industrial environments.
This role is ideal for candidates who want deep infrastructure ownership at a company where uptime, latency, and reliability directly affect physical operations — not just software. You'll partner closely with AI, data, and product engineering teams to make sure the systems they build can actually run in production, safely and at scale.
What You'll Do
Own and evolve Nexxa's core infrastructure — compute, networking, storage, and deployment systems — end-to-end
Design and operate CI/CD pipelines that support fast, safe iteration across AI, data, and product engineering teams
Build and maintain infrastructure-as-code (e.g., Terraform, Pulumi) for reproducible, auditable environments across cloud and on-prem/edge deployments
Architect and manage Kubernetes-based platforms for training, inference, and application workloads, including GPU scheduling and autoscaling
Partner with data and AI teams to support the infrastructure behind:
Data warehouses and lakehouse architectures (e.g., Snowflake, BigQuery, Redshift, Databricks)
Feature stores, embedding indices, and retrieval pipelines
Model training, evaluation, and serving infrastructure
Define and drive observability practices — metrics, logging, tracing, and alerting — across distributed systems
Establish and enforce reliability practices: SLOs/SLIs, incident response, postmortems, and on-call rotations
Design for security and compliance across cloud infrastructure, secrets management, and access control, particularly relevant to industrial and legacy-environment integrations
Make pragmatic tradeoffs across cost, latency, reliability, and developer velocity
Collaborate with engineering leadership to define infrastructure roadmap and platform strategy
Mentor engineers on infrastructure best practices and raise the bar for operational excellence across the org
Required Qualifications
6+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or infrastructure-focused software engineering roles
Deep hands-on experience with:
Cloud platforms (AWS, GCP, or Azure) at production scale
Kubernetes in production, including GPU workload scheduling
Infrastructure-as-code tooling (Terraform, Pulumi, or equivalent)
CI/CD systems (e.g., GitHub Actions, GitLab CI, CircleCI, Jenkins, ArgoCD)
Strong track record designing and operating observability stacks (e.g., Prometheus, Grafana, Datadog, OpenTelemetry)
Experience supporting ML/AI infrastructure — training clusters, model serving, data pipelines — a strong plus
Excellent scripting/programming skills (Python, Go, or Bash) for automation and tooling
Proven ability to independently scope and lead infrastructure projects from design through production rollout
Strong incident management instincts — you can lead through an outage calmly and drive toward root cause
Preferred Qualifications
Experience operating infrastructure that bridges cloud and edge/on-prem environments, especially in industrial or manufacturing contexts
Familiarity with data warehouse/lakehouse platforms (Snowflake, BigQuery, Redshift, Databricks)
Experience with service mesh, zero-trust networking, or compliance frameworks relevant to industrial/critical infrastructure (e.g., SOC 2, IEC 62443)
History of building internal developer platforms or self-service infrastructure tooling
Experience scaling infrastructure teams or setting technical direction at a Staff level
What Success Looks Like
You can own ambiguous, high-stakes infrastructure problems end-to-end
Systems you build stay reliable as usage and scale grow — you design for the next order of magnitude, not just today
You bring strong technical judgment on tradeoffs between reliability, cost, and speed
You raise the bar for operational rigor and engineering discipline across the team
You help define what's next for the platform, not just execute what's known
Why Join Nexxa.ai?
Innovative Environment: Play a critical role in transforming heavy industries through groundbreaking AI and automation technologies
Collaborative Culture: Be part of a team that values innovation, discipline, and continuous improvement
Professional Growth: Benefit from significant opportunities for career development and advancement
Competitive Compensation: Enjoy a comprehensive salary and equity package reflective of your expertise and contributions
If you're passionate about building the infrastructure that powers advanced AI solutions in the real world, we'd love to connect.