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במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • אלפי משרות חדשות בכל יום
חינם. בלי פרסומות. בלי אותיות קטנות.
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כבר העליתם קו"ח בעבר? כניסה
מלאה
25,000-35,000 ₪
What You Will Be Doing
Own the co-build agenda with AWS & GCP
Drive our active co-build initiatives with AWS/GCP product and engineering teams from scoping through launch.
Own the technical relationship with AWS/GCP product managers and engineers on the EKS/GKE, Karpenter, and container services teams. Be the person they call, and the person who can answer without scheduling a follow-up.
Track the EKS/GKE and AI/ML roadmap closely enough to tell us what it means. Dynamic Resource Allocation, MIG and time-slicing landing in Karpenter and Auto Mode/Auto Pilot, managed control plane work, and pod isolation all move the ground under our product. You will be the first person to see it coming.
Continuously validate that we run on where AWS/GCP are going, not just where it is. As AWS/GCP abstracts the node further, our agent, our scheduler, and especially our GPU device plugin need to keep working. Confirming that, early, is a standing part of the job.
Bring AWS/GCP requirements and constraints back into R&D as real engineering input, and represent our architecture back to AWS/GCP accurately enough that they design around it.
Look for opportunities to be a design partner and later a launch partner.
Technical depth on us and EKS/GKE
Be the person who can explain how we work on EKS/GKE to any technical audience, without an SE in the room: real-time pod right-sizing, HPA and replica management, intelligent pod placement, Karpenter and node optimization, Spot, and GPU fractionalization and right-sizing for inference workloads.
Hold your own with AWS/GKE Solutions Architects and customer platform engineers on scheduling, autoscaling, resource management, and where our approach differs from static MIG and time-slicing.
Own the co-build agenda with AWS & GCP
Drive our active co-build initiatives with AWS/GCP product and engineering teams from scoping through launch.
Own the technical relationship with AWS/GCP product managers and engineers on the EKS/GKE, Karpenter, and container services teams. Be the person they call, and the person who can answer without scheduling a follow-up.
Track the EKS/GKE and AI/ML roadmap closely enough to tell us what it means. Dynamic Resource Allocation, MIG and time-slicing landing in Karpenter and Auto Mode/Auto Pilot, managed control plane work, and pod isolation all move the ground under our product. You will be the first person to see it coming.
Continuously validate that we run on where AWS/GCP are going, not just where it is. As AWS/GCP abstracts the node further, our agent, our scheduler, and especially our GPU device plugin need to keep working. Confirming that, early, is a standing part of the job.
Bring AWS/GCP requirements and constraints back into R&D as real engineering input, and represent our architecture back to AWS/GCP accurately enough that they design around it.
Look for opportunities to be a design partner and later a launch partner.
Technical depth on us and EKS/GKE
Be the person who can explain how we work on EKS/GKE to any technical audience, without an SE in the room: real-time pod right-sizing, HPA and replica management, intelligent pod placement, Karpenter and node optimization, Spot, and GPU fractionalization and right-sizing for inference workloads.
Hold your own with AWS/GKE Solutions Architects and customer platform engineers on scheduling, autoscaling, resource management, and where our approach differs from static MIG and time-slicing.
Requirements:
What You Bring
5+ years in a customer-facing or partner-facing technical role: Solutions Architect, Solutions Engineer, Partner Solutions Architect, Technical Account Manager, or platform engineering with significant external exposure. Time inside AWS/GCP in an SA, PSA, or TAM role is ideal.
Deep, current Kubernetes expertise. Not conceptual. You have run or architected production Kubernetes, and you can go deep on scheduling, autoscaling, requests and limits, resource contention, and what Karpenter does and does not solve. If your hands-on work was a decade ago, this is not the role.
Strong working knowledge of EKS/GKE specifically, and of the AWS/GKE compute stack around it: EC2, instance families, Spot, and GPU instances.
Real experience with the cloud-native ecosystem: containers, Helm, operators, GitOps, observability, and the operational realities of running Kubernetes at scale.
Demonstrated ability to work directly with software engineers as a peer. You can hold a design conversation, understand a trade-off, and carry it accurately to a third party.
Ability to translate in both directions: engineering constraints into partner-facing language, and partner requirements into scoped engineering work.
Excellent written and spoken English, including with executive audiences.
Self-starter with strong ownership and follow-through. This role succeeds or fails on things actually shipping.
Nice to Have
Hands-on experience with GPU workloads on Kubernetes: inference serving, vLLM, MIG, time-slicing, device plugins, or Dynamic Resource Allocation.
Experience taking a product through AWS technical validation, a Foundational Technical Review, or a service integration with an AWS service team.
Familiarity with AWS/GCP Marketplace mechanics: container and SaaS listings, the metering and entitlement APIs, private offers, and free trials.
Experience as a launch partner on a cloud provider product release.
Contributions to Kubernetes or CNCF projects, or a public technical presence such as talks, blog posts, or open source work.
Familiarity with AWS competency requirements.
What You Bring
5+ years in a customer-facing or partner-facing technical role: Solutions Architect, Solutions Engineer, Partner Solutions Architect, Technical Account Manager, or platform engineering with significant external exposure. Time inside AWS/GCP in an SA, PSA, or TAM role is ideal.
Deep, current Kubernetes expertise. Not conceptual. You have run or architected production Kubernetes, and you can go deep on scheduling, autoscaling, requests and limits, resource contention, and what Karpenter does and does not solve. If your hands-on work was a decade ago, this is not the role.
Strong working knowledge of EKS/GKE specifically, and of the AWS/GKE compute stack around it: EC2, instance families, Spot, and GPU instances.
Real experience with the cloud-native ecosystem: containers, Helm, operators, GitOps, observability, and the operational realities of running Kubernetes at scale.
Demonstrated ability to work directly with software engineers as a peer. You can hold a design conversation, understand a trade-off, and carry it accurately to a third party.
Ability to translate in both directions: engineering constraints into partner-facing language, and partner requirements into scoped engineering work.
Excellent written and spoken English, including with executive audiences.
Self-starter with strong ownership and follow-through. This role succeeds or fails on things actually shipping.
Nice to Have
Hands-on experience with GPU workloads on Kubernetes: inference serving, vLLM, MIG, time-slicing, device plugins, or Dynamic Resource Allocation.
Experience taking a product through AWS technical validation, a Foundational Technical Review, or a service integration with an AWS service team.
Familiarity with AWS/GCP Marketplace mechanics: container and SaaS listings, the metering and entitlement APIs, private offers, and free trials.
Experience as a launch partner on a cloud provider product release.
Contributions to Kubernetes or CNCF projects, or a public technical presence such as talks, blog posts, or open source work.
Familiarity with AWS competency requirements.
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • אלפי משרות חדשות בכל יום
חינם. בלי פרסומות. בלי אותיות קטנות.
DOCX, DOC, PDF - בעברית או באנגלית
כבר העליתם קו"ח בעבר? כניסה
