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Infrastructure Engineer/SRE

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Remote from
Canada
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
27 Nov 2026
Listing views
35
Application actions
3
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AI Summary

The role, at a glance.

Cresta is seeking an experienced Infrastructure Engineer/SRE to build and operate reliable, secure multi-cloud infrastructure for its AI platform. The role focuses on Kubernetes operations, infrastructure as code, observability, CI/CD, developer tooling, and automation across AWS and other cloud providers. The engineer will also help develop machine-learning infrastructure for training, testing, and deploying workloads on large-scale datasets. This is a highly autonomous senior technical role requiring strong production experience with cloud platforms, container security, and platform engineering. The position is remote within Canada and is offered on a full-time basis.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role requires 5+ years of production DevOps/SRE experience and deep expertise across Kubernetes, cloud infrastructure, security, IaC, and automation. Supporting multi-cloud systems and ML infrastructure creates substantial operational breadth and reliability responsibility.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Highly competitive
$180,000
US market range (per year)$150k–$210k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary range is disclosed. The yearly compensation estimate is an AI-generated USD market estimate for a senior Infrastructure Engineer/SRE with Kubernetes, multi-cloud, security, and ML-platform responsibilities; it is not verified employer compensation.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe how you would improve reliability for a multi-cloud Kubernetes platform.

I would begin by defining service-level objectives and identifying the critical workloads and failure modes. I would standardize cluster configuration through infrastructure as code, implement automated health checks and alerting, test backup and recovery processes, and design workload placement and failover policies appropriate to each service's availability needs.

How have you used Terraform or another IaC tool to make infrastructure changes safer?

I use reusable modules, code review, remote state with locking, environment separation, and automated plan/apply pipelines with approval controls. I also validate policy and security requirements before deployment, which reduces configuration drift and makes changes auditable and repeatable.

What practices would you implement to secure containerized workloads on Kubernetes?

I would use minimal and regularly scanned images, enforce image provenance, avoid privileged containers, apply least-privilege RBAC, manage secrets securely, and use network policies to limit service communication. I would also apply admission controls and continuously monitor runtime activity and cluster audit logs.

How would you design observability for a production platform used by engineering and ML teams?

I would establish consistent metrics, structured logs, distributed traces, and dashboards tied to user-facing service-level objectives. Alerts should be actionable and routed with runbooks, while capacity, deployment, and security signals should be visible across infrastructure and application layers.

Give an example of an operational task you would prioritize automating.

I would prioritize repetitive, error-prone tasks with meaningful incident or developer-time impact, such as provisioning namespaces and access controls for new services. An automated workflow using approved templates, policy checks, and GitOps deployment would make the process faster, consistent, and auditable.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.

Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu, founded and led Google’s Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.

Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.

About the role:

As a member of the infrastructure team you are responsible for designing, building, and advancing our core infrastructure that allows the engineering team to execute quickly, productively, and securely. You will join a collaborative but highly autonomous working environment in which each member has a defined role with clear expectations, as well as the freedom to pursue projects they find interesting.

Responsibilities:

  • Developer Toolchain. Partner with engineers to build dev tools that empower developer workflows and deployment infrastructure.
  • Ensure reliability of multi-cloud Kubernetes clusters and pipelines.
  • Metrics, logging, analytics, and alerting for performance and security across all endpoints and applications.
  • Infrastructure-as-code deployment tooling and supporting services on multiple cloud providers.
  • Automate operations and engineering. Focus on automation so we can spend energy where it matters.
  • Building machine learning infrastructure that enables AI teams to train, test, and deploy on large-scale datasets.

What we are looking for:

  • 5+ years experience in DevOps, Site Reliability Engineering, Production Engineering, or equivalent field.
  • Deep proficiency with coding languages such as Golang or Python.
  • Deep familiarity with container-related security best practices.
  • Production experience working with Kubernetes, and a deep understanding of the Kubernetes ecosystem, including popular open-source tooling such as cert-manager or external-dns. Experience with GPU-enabled clusters is a bonus.
  • Production experience with Kubernetes templating tools such as Helm or Kustomize.
  • Production experience with IAC tools such as Terraform or CloudFormation.
  • Production experience working with AWS and services such as IAM, S3, EC2, and EKS.
  • Production experience with other cloud providers such as Google Cloud and Azure is a bonus.
  • Production experience with database software such as PostgreSQL
  • Experience with GitOps tooling such as Flux or Argo.
  • Experience with CI/CD such as GitHub Actions.

Perks & Benefits:

  • We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
  • Paid parental leave to support you and your family
  • Monthly Health & Wellness allowance
  • Work from home office stipend to help you succeed in a remote environment
  • Lunch reimbursement for in-office employees
  • PTO: 3 weeks in Canada

Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. Your recruiter can provide further details.

This posting will be used to fill a newly-created role.

Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email).

Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed.

Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates’ personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.

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