Staff Network Engineer, App Platform

Posted Yesterday
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San Francisco, CA, USA
In-Office
1-1 Annually
Senior level
Artificial Intelligence • Big Data • Machine Learning
The Data Platform for AI: High quality training and validation data for AI applications.
The Role
Own the network architecture and standards for a multi-cloud generative AI platform deployed across AWS, Azure, GCP, and customer environments. Design VPCs, routing, private connectivity, DNS, ingress, egress, edge configurations, Kubernetes networking, service mesh, and network policies. Establish repeatable customer-boundary connectivity and access patterns, review proposed solutions, partner on security and compliance, debug hybrid-cloud incidents, and document operational standards. The role serves as the central networking authority across regulated and air-gapped deployments.
Summary Generated by Built In

Scale GP (Scale Generative AI Platform) is Scale’s enterprise AI platform, providing APIs and infrastructure for knowledge retrieval, inference, evaluation, agents, and more. We deploy SGP across AWS, Azure, and GCP, often directly into customer-controlled cloud environments across highly regulated industries including healthcare, financial services, telecom, and retail.

As SGP has grown in scale and complexity, networking has become a critical architectural discipline of its own. Today, teams routinely encounter the same hard problems — VPC design, routing, ingress and egress, private connectivity, service exposure, address-space constraints, firewall policies, and cross-environment communication — but solve them differently depending on the deployment. We’re looking for a Senior Network Engineer to establish the architectural standards for how SGP connects to customer infrastructure and how traffic moves throughout the platform.

You’ll own network architecture across a large and rapidly growing fleet of Kubernetes environments spanning AWS, Azure, and GCP, with many deployed inside customer-owned cloud accounts and networks that we do not control. The constraints vary significantly: a commercial deployment behind a customer-managed API gateway; a hub-and-spoke enterprise network where the customer assigns our address space; a GovCloud environment protected by default-deny firewall policies; or a fully air-gapped deployment with no external connectivity.

The goal is not to create a bespoke network architecture for every customer. Your job is to define one clear, secure, and supportable networking model for SGP — and establish the small set of defensible variations required to operate across different clouds, customer architectures, and compliance regimes.

What You'll Do
  • Own network architecture for the SGP platform: define and enforce network standards across cloud environments (AWS, Azure, GCP) and customer deployments
  • Design and review VPC architectures, peering, DNS, load balancing, and CDN/edge configurations (e.g., Cloudflare), grounding root-cause and tradeoff discussions in data and domain depth
  • Bring strong technical judgment to VPN, routing, access, ingress/egress, and traffic-flow decisions
  • Review proposed networking solutions from platform, product, and forward-deployed teams; evaluate what should and should not be introduced into the platform boundary
  • Define the standard connectivity pattern between Scale's control plane and customer data planes (VPC peering, PrivateLink/Private Service Connect, site-to-site VPN, reverse tunnels) — and converge today's per-customer designs onto it
  • Own the customer-boundary delivery blueprint: how code, images, and traffic cross into a customer tenant — CI/CD mirroring across org boundaries (including customer-side Azure DevOps), artifact scan gates, private registries, ingress — so new engagements configure a pattern instead of designing one
  • Own engineer access into customer and internal environments (Tailscale/Teleport/bastion-class decisions), replacing per-engineer VPN sprawl and hand-rolled tunnels with something auditable
  • Own the Kubernetes traffic layer: Istio/Envoy mesh and ingress, the per-cloud CNI matrix, and a portable NetworkPolicy contract that constrains egress for thousands of short-lived agent-sandbox pods running untrusted code
  • Reduce rework by preventing one-off implementations from becoming long-term platform burden
  • Partner with security engineering on network segmentation, zero-trust access, and compliance requirements in regulated customer environments
  • Debug complex connectivity, latency, and traffic-flow issues across hybrid and multi-cloud deployments
  • Document network architecture, standards, and runbooks so adjacent teams can operate confidently
What We're Looking For
  • 5+ years of network engineering experience, including designing and operating production networks in cloud environments
  • Deep expertise in cloud networking on at least two of AWS, Azure, and GCP: VPC design, peering, Transit Gateway/hub-and-spoke topologies, private connectivity (PrivateLink, Private Service Connect), and DNS
  • Kubernetes networking depth — CNI, ingress, NetworkPolicy, service mesh (Istio/Envoy) — this is where most of our real incidents live
  • Strong fundamentals in TCP/IP, BGP, routing, firewalls, VPN (site-to-site and client), and TLS
  • Experience with edge/CDN and traffic-management platforms such as Cloudflare
  • Has defined a network standard or reference architecture that other teams adopted, and enforced it through design review
  • Comfortable as the sole domain owner: able to collect requirements across five-plus live environments you didn't design, then converge them without breaking any
  • Has made build-vs-adopt networking calls with vendor-support or contractual consequences in a customer's cloud
  • Infrastructure-as-code proficiency (Terraform preferred)
  • Familiarity with network security and compliance requirements in regulated industries (healthcare, finance, government), including environments across multiple compliance regimes (commercial, FedRAMP/GovCloud, air-gapped), is a plus
  • Excellent communication skills — able to explain networking tradeoffs to both technical and non-technical audiences and influence decisions without direct authority
Why This Role Matters

Without a dedicated owner, adjacent teams are covering a domain that needs specialized expertise. You will be the point of accountability for network architecture as SGP grows — raising the quality of every deployment, unblocking confident decisions, and keeping the platform boundary clean as we scale.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$1$1 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Skills Required

  • 5+ years of network engineering experience, including designing and operating production cloud networks
  • Deep cloud networking expertise in at least two of AWS, Azure, and GCP, including VPC design, peering, hub-and-spoke topologies, private connectivity, and DNS
  • Kubernetes networking experience with CNI, ingress, NetworkPolicy, and Istio or Envoy service mesh
  • Strong TCP/IP, BGP, routing, firewall, VPN, and TLS fundamentals
  • Experience with edge, CDN, and traffic-management platforms such as Cloudflare
  • Experience defining and enforcing network standards or reference architectures through design review
  • Ability to independently own networking across multiple existing production environments and converge designs without disrupting operations
  • Experience making build-versus-adopt networking decisions with vendor-support or contractual consequences
  • Excellent communication skills and ability to influence technical and non-technical stakeholders without direct authority
  • Infrastructure-as-code proficiency, preferably Terraform
  • Familiarity with network security and compliance requirements in healthcare, finance, government, FedRAMP, GovCloud, and air-gapped environments

Scale AI Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Scale AI and has not been reviewed or approved by Scale AI.

  • Healthcare Strength Company materials and third‑party pages describe comprehensive medical, dental, and vision coverage along with mental‑health services and an EAP. Health insurance is portrayed as strong, with options like HSA/FSA and indications of high premium coverage.
  • Leave & Time Off Breadth Descriptions highlight generous PTO, paid holidays and sick time, bereavement, volunteer time, and role‑dependent flexibility or remote options. This breadth is positioned as part of a supportive time‑off approach, with specifics varying by location.
  • Equity Value & Accessibility Full‑time offers commonly include equity and an ESPP, which can meaningfully lift total compensation, especially in engineering and senior roles. Job postings and compensation snapshots consistently reference base‑plus‑equity packages aligned with competitive AI market pay.

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The Company
HQ: San Francisco, CA
523 Employees
Year Founded: 2016

What We Do

Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.

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