Cloud Engineer/Site Reliability Architect
Slalom · Las Vegas, NV · 1 mo ago
Engineering$149k–$185k/yrFull-time
We need to output HTML fragment with sections: headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include only sections with real content.
We have job description: It's a Kubernetes-heavy platform engineering role. The posting includes:
- Intro paragraph: "This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly."
- Then "What You’ll Do" bullet list.
- Then "What You’ll Bring" bullet list.
- Then "About Us" paragraph.
- Then "Compensation and Benefits" with details: benefits list, compensation ranges.
- Then EEO etc which we must remove.
We need to map to sections: About the role (intro), Responsibilities (What You’ll Do), Requirements/Qualifications/Skills (What You’ll Bring maybe split into Requirements and Skills). Benefits and Pay sections.
We must not repeat job title as heading. No Job ID.
We must not include boilerplate like EEO, accommodation request, etc.
We must not include application instructions (like "We will accept applicants until 10/5/2026...") Actually that is part of posting but maybe considered application instruction? It says "We will accept applicants until 10/5/2026, or until the position is filled." That's like a deadline; could be considered application instruction. The instruction says remove application instructions. So we should remove that line. Also remove contact email for pay questions? That might be considered part of compensation? It's contact for pay range questions; maybe keep as part of Compensation? But it's more like contact. Safer to remove? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The contact email for pay questions is not exactly application instruction but could be considered part of compensation info. Might keep? However it's a contact for questions about pay range; could be considered part of Compensation section. I'd keep it as a paragraph under Compensation.
We also need to remove duplicated lines: The posting repeats "The target base salary range for Senior Consultant in is $149,000-$185,000." That seems a duplicate with missing location. We should keep only meaningful ranges.
We need to preserve all substantive information.
Let's extract content:
Intro: "This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly."
Responsibilities (What You’ll Do):
- Operate Kubernetes platforms at significant scale across providers, including Amazon Elastic Kubernetes Service (EKS), CoreWeave Kubernetes Service (CKS), and Google Kubernetes Engine (GKE).
- Own the Kubernetes cluster lifecycle, including node-pool design and management, scheduler troubleshooting, container network interface (CNI) and network-policy troubleshooting, capacity planning, and safe rolling upgrades across large fleets.
- Develop, review, and maintain infrastructure as code with Terraform, along with Python tooling and automation that improve reliability, repeatability, and operational efficiency.
- Define and maintain service-level indicators (SLIs) and service-level objectives (SLOs); build monitoring and alerting that surface meaningful risks before they affect workloads.
- Debug complex distributed-system failures by forming hypotheses, testing them methodically, and separating temporal correlation from causation.
- Provision high-performance computing (HPC) and GPU infrastructure through the Conveyor CI/CD system across AWS, CoreWeave, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), with additional providers as the platform expands.
- Coordinate daily with Networking, Storage, Security, and AI/ML platform teams to resolve cross-system dependencies and improve the end-to-end developer and researcher experience.
- Bring forward well-reasoned proposals, solutions, and informed opinions; use available tools and resources to self-unblock and drive issues to resolution.
What You’ll Bring (Requirements/Skills):
- Hands-on Kubernetes experience including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across fleets.
- Strong Terraform proficiency and experience writing and reviewing production infrastructure as code on a daily basis.
- Practical Python skills for tooling and automation, including the ability to write code without relying on artificial intelligence assistance.
- Strong critical-thinking and debugging skills, with a disciplined approach to forming hypotheses, validating evidence, and isolating root causes.
- Ability to read unfamiliar code, understand its behavior, and diagnose issues effectively.
- Resourcefulness and a consistent ability to self-unblock using documentation, telemetry, code, peers, and available tooling.
- A proactive working style: you arrive with proposals, formulate solutions, and communicate informed technical opinions.
- Clear communication and effective collaboration across engineering teams and technical stakeholders.
- Working knowledge of AWS or similar Cloud services relevant to compute and data-intensive platforms, including Amazon EC2, Amazon S3, Amazon EFS, and Amazon FSx for Lustre.
- Experience designing or operating CI/CD pipelines and automated infrastructure provisioning workflows.
- Knowledge of cloud networking, storage, security, observability, reliability engineering, and platform governance.
- Nice-to-have: Experience using AI coding tools responsibly: you remain accountable for the solution, validate generated code, identify edge cases, and reject unnecessary or incorrect output.
About Us:
- Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to co-create powerful customer experiences, modern ways of working, and meaningful impact. What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. That’s why we prioritize purpose, flexibility, connection, and recognition, so our people can thrive and love what they do, most days.
Compensation and Benefits:
- Benefits: meaningful time off and paid holidays, parental leave, 401(k) with a match, a range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, short/long-term disability, yearly $350 reimbursement account for any well-being-related expenses, discounted home, auto, and pet insurance.
- Pay: target base salary ranges:
- Senior Consultant in East Bay, Silicon Valley, and San Francisco: $149,000-$185,000.
- Senior Consultant in [missing location?] maybe duplicate; we can ignore the empty one.
- Senior Consultant in San Diego, Los Angeles, Orange County, Seattle, Houston, New Jersey, New York City, Westchester, Boston, Washington DC: $136,500-$169,500.
- Senior Consultant in all other US based Slalom locations: $125,000-$155,500.
- Individuals may be eligible for an annual discretionary bonus.
- Actual compensation will depend upon an individual’s skills, experience, qualifications, location, and other relevant factors.
- The salary pay range is subject to change and may be modified at any time.
- We are committed to pay transparency and compliance with applicable laws. If you have questions or concerns about the pay range or other compensation information in this posting, please contact us at: peopleone@slalom.com. Please note, this recipient is not able to support recruitment inquiries beyond this purpose.
We should remove the line about contact? It's part of compensation info; maybe keep as a note. But it's not boilerplate; it's specific contact for pay questions. I'd keep it.
We must not include EEO etc.
Now produce HTML.
We need sections: About the role (intro), Responsibilities, Requirements (maybe combine What You’ll Bring into Requirements and Skills? Could split: Requirements (hands-on experience, Terraform, Python, critical-thinking, etc.) and Skills (maybe the nice-to-have). But we can also just have Requirements section covering all. The instruction: prefer a few substantive sections over many thin ones. So we could have About the role, Responsibilities, Requirements, Benefits, Pay. That's 5 sections.
We need to use
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include only sections with real content.
We have job description: It's a Kubernetes-heavy platform engineering role. The posting includes:
- Intro paragraph: "This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly."
- Then "What You’ll Do" bullet list.
- Then "What You’ll Bring" bullet list.
- Then "About Us" paragraph.
- Then "Compensation and Benefits" with details: benefits list, compensation ranges.
- Then EEO etc which we must remove.
We need to map to sections: About the role (intro), Responsibilities (What You’ll Do), Requirements/Qualifications/Skills (What You’ll Bring maybe split into Requirements and Skills). Benefits and Pay sections.
We must not repeat job title as heading. No Job ID.
We must not include boilerplate like EEO, accommodation request, etc.
We must not include application instructions (like "We will accept applicants until 10/5/2026...") Actually that is part of posting but maybe considered application instruction? It says "We will accept applicants until 10/5/2026, or until the position is filled." That's like a deadline; could be considered application instruction. The instruction says remove application instructions. So we should remove that line. Also remove contact email for pay questions? That might be considered part of compensation? It's contact for pay range questions; maybe keep as part of Compensation? But it's more like contact. Safer to remove? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The contact email for pay questions is not exactly application instruction but could be considered part of compensation info. Might keep? However it's a contact for questions about pay range; could be considered part of Compensation section. I'd keep it as a paragraph under Compensation.
We also need to remove duplicated lines: The posting repeats "The target base salary range for Senior Consultant in is $149,000-$185,000." That seems a duplicate with missing location. We should keep only meaningful ranges.
We need to preserve all substantive information.
Let's extract content:
Intro: "This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly."
Responsibilities (What You’ll Do):
- Operate Kubernetes platforms at significant scale across providers, including Amazon Elastic Kubernetes Service (EKS), CoreWeave Kubernetes Service (CKS), and Google Kubernetes Engine (GKE).
- Own the Kubernetes cluster lifecycle, including node-pool design and management, scheduler troubleshooting, container network interface (CNI) and network-policy troubleshooting, capacity planning, and safe rolling upgrades across large fleets.
- Develop, review, and maintain infrastructure as code with Terraform, along with Python tooling and automation that improve reliability, repeatability, and operational efficiency.
- Define and maintain service-level indicators (SLIs) and service-level objectives (SLOs); build monitoring and alerting that surface meaningful risks before they affect workloads.
- Debug complex distributed-system failures by forming hypotheses, testing them methodically, and separating temporal correlation from causation.
- Provision high-performance computing (HPC) and GPU infrastructure through the Conveyor CI/CD system across AWS, CoreWeave, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), with additional providers as the platform expands.
- Coordinate daily with Networking, Storage, Security, and AI/ML platform teams to resolve cross-system dependencies and improve the end-to-end developer and researcher experience.
- Bring forward well-reasoned proposals, solutions, and informed opinions; use available tools and resources to self-unblock and drive issues to resolution.
What You’ll Bring (Requirements/Skills):
- Hands-on Kubernetes experience including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across fleets.
- Strong Terraform proficiency and experience writing and reviewing production infrastructure as code on a daily basis.
- Practical Python skills for tooling and automation, including the ability to write code without relying on artificial intelligence assistance.
- Strong critical-thinking and debugging skills, with a disciplined approach to forming hypotheses, validating evidence, and isolating root causes.
- Ability to read unfamiliar code, understand its behavior, and diagnose issues effectively.
- Resourcefulness and a consistent ability to self-unblock using documentation, telemetry, code, peers, and available tooling.
- A proactive working style: you arrive with proposals, formulate solutions, and communicate informed technical opinions.
- Clear communication and effective collaboration across engineering teams and technical stakeholders.
- Working knowledge of AWS or similar Cloud services relevant to compute and data-intensive platforms, including Amazon EC2, Amazon S3, Amazon EFS, and Amazon FSx for Lustre.
- Experience designing or operating CI/CD pipelines and automated infrastructure provisioning workflows.
- Knowledge of cloud networking, storage, security, observability, reliability engineering, and platform governance.
- Nice-to-have: Experience using AI coding tools responsibly: you remain accountable for the solution, validate generated code, identify edge cases, and reject unnecessary or incorrect output.
About Us:
- Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to co-create powerful customer experiences, modern ways of working, and meaningful impact. What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. That’s why we prioritize purpose, flexibility, connection, and recognition, so our people can thrive and love what they do, most days.
Compensation and Benefits:
- Benefits: meaningful time off and paid holidays, parental leave, 401(k) with a match, a range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, short/long-term disability, yearly $350 reimbursement account for any well-being-related expenses, discounted home, auto, and pet insurance.
- Pay: target base salary ranges:
- Senior Consultant in East Bay, Silicon Valley, and San Francisco: $149,000-$185,000.
- Senior Consultant in [missing location?] maybe duplicate; we can ignore the empty one.
- Senior Consultant in San Diego, Los Angeles, Orange County, Seattle, Houston, New Jersey, New York City, Westchester, Boston, Washington DC: $136,500-$169,500.
- Senior Consultant in all other US based Slalom locations: $125,000-$155,500.
- Individuals may be eligible for an annual discretionary bonus.
- Actual compensation will depend upon an individual’s skills, experience, qualifications, location, and other relevant factors.
- The salary pay range is subject to change and may be modified at any time.
- We are committed to pay transparency and compliance with applicable laws. If you have questions or concerns about the pay range or other compensation information in this posting, please contact us at: peopleone@slalom.com. Please note, this recipient is not able to support recruitment inquiries beyond this purpose.
We should remove the line about contact? It's part of compensation info; maybe keep as a note. But it's not boilerplate; it's specific contact for pay questions. I'd keep it.
We must not include EEO etc.
Now produce HTML.
We need sections: About the role (intro), Responsibilities, Requirements (maybe combine What You’ll Bring into Requirements and Skills? Could split: Requirements (hands-on experience, Terraform, Python, critical-thinking, etc.) and Skills (maybe the nice-to-have). But we can also just have Requirements section covering all. The instruction: prefer a few substantive sections over many thin ones. So we could have About the role, Responsibilities, Requirements, Benefits, Pay. That's 5 sections.
We need to use for each section heading.
Inside each section, use
for prose,
- for lists.
We must not repeat job title as heading.
Let's craft:
not needed; just output HTML fragment.
We'll do:
About the role
This is a Kubernetes-heavy platform engineering role supporting large-scale, multi-cloud GPU infrastructure. Success requires deep operational judgment, disciplined debugging, strong automation skills, and the ability to protect platform stability while capacity grows rapidly.
Responsibilities
- Operate Kubernetes platforms at significant scale across providers, including Amazon Elastic Kubernetes Service (EKS), CoreWeave Kubernetes Service (CKS), and Google Kubernetes Engine (GKE).
- Own the Kubernetes cluster lifecycle, including node-pool design and management, scheduler troubleshooting, container network interface (CNI) and network-policy troubleshooting, capacity planning, and safe rolling upgrades across large fleets.
- Develop, review, and maintain infrastructure as code with Terraform, along with Python tooling and automation that improve reliability, repeatability, and operational efficiency.
- Define and maintain service-level indicators (SLIs) and service-level objectives (SLOs); build monitoring and alerting that surface meaningful risks before they affect workloads.
- Debug complex distributed-system failures by forming hypotheses, testing them methodically, and separating temporal correlation from causation.
- Provision high-performance computing (HPC) and GPU infrastructure through the Conveyor CI/CD system across AWS, CoreWeave, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), with additional providers as the platform expands.
- Coordinate daily with Networking, Storage, Security, and AI/ML platform teams to resolve cross-system dependencies and improve the end-to-end developer and researcher experience.
- Bring forward well-reasoned proposals, solutions, and informed opinions; use available tools and resources to self-unblock and drive issues to resolution.
Requirements
- Hands-on Kubernetes experience including node pool sizing, scheduler debugging, CNI troubleshooting, and rolling upgrades across fleets.
- Strong Terraform proficiency and experience writing and reviewing production infrastructure as code on a daily basis.
- Practical Python skills for tooling and automation, including the ability to write code without relying on artificial intelligence assistance.
- Strong critical-thinking and debugging skills, with a disciplined approach to forming hypotheses, validating evidence, and isolating root causes.
- Ability to read unfamiliar code, understand its behavior, and diagnose issues effectively.
- Resourcefulness and a consistent ability to self-unblock using documentation, telemetry, code, peers, and available tooling.
- A proactive working style: you arrive with proposals, formulate solutions, and communicate informed technical opinions.
- Clear communication and effective collaboration across engineering teams and technical stakeholders.
- Working knowledge of AWS or similar Cloud services relevant to compute and data-intensive platforms, including Amazon EC2, Amazon S3, Amazon EFS, and Amazon FSx for Lustre.
- Experience designing or operating CI/CD pipelines and automated infrastructure provisioning workflows.
- Knowledge of cloud networking, storage, security, observability, reliability engineering, and platform governance.
- Nice-to-have: Experience using AI coding tools responsibly: you remain accountable for the solution, validate generated code, identify edge cases, and reject unnecessary or incorrect output.
Benefits
- Meaningful time off and paid holidays
- Parental leave
- 401(k) with a match