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 RoleWe'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 DoOwn 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
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
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
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
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.
