דרושים » מחשבים ורשתות » Infra Engineer

We are looking for a Senior DevOps Engineer who thrives in high-scale, high-performance environments. In this role, you will design and manage mission-critical infrastructure, develop automation tools, and ensure the reliability and scalability of platform. You will work closely with engineering teams to optimize performance, enhance observability, and prevent incidents before they happen.

If you love solving complex infrastructure challenges and building tools that empower engineers, this role is for you!

What Will You Do?
As a Senior DevOps Engineer , you will:

Design, build, and maintain a highly available, scalable, and resilient production infrastructure handling millions of requests per second.
Manage and optimize tens of AWS accounts in a multi-account cloud environment.
Developing AI-driven automation frameworks and tools that more than 400 R&D engineers use while enhancing system reliability and engineering efficiency.
Design, implement, and support the LLM and agentic workflow infrastructure, ensuring its scalability and reliability.
Manage thousands of servers and containers, ensuring seamless infrastructure operations.
Improve and maintain our logging, monitoring, and alerting stacks for enhanced observability.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Collaborate with engineering teams to optimize performance, reduce latency, and improve deployment processes.

Were looking for a Senior Infrastructure Engineer who views "Infrastructure as Software." In 2026, we dont just manage servers; we build high-performance environments that allow multi-agent systems to operate at scale.
You will be a core member of the R&D team, blending deep DevOps expertise with the coding rigor of a Backend Engineer. You arent just "configuring" AWS; you are architecting the distributed systems and data pipelines that power our autonomous security brain. Your mission is to ensure that while our agents are evolving and taking actions, our underlying platform remains immutable, observable, and infinitely scalable.
What You'll Do
Design, build, and operate our company's cloud infrastructure using AWS, Kubernetes, and Infrastructure as Code.
Build internal tools and platform services using Python and Go to improve developer productivity and system reliability.
Own infrastructure automation with Terraform, Pulumi, and modern cloud-native tooling.
Partner closely with Backend, Data Science, and Security Engineering teams to build scalable, reliable platforms.
Improve observability, monitoring, and incident response across distributed production systems.
Design and optimize infrastructure for performance, scalability, security, and cost efficiency.
Help shape engineering best practices, platform architecture, and developer experience as our company continues to grow.

We are looking for a Senior DevOps Engineer who thrives in high-scale, high-performance environments. In this role, you will design and manage mission-critical infrastructure, develop automation tools, and ensure the reliability and scalability of platform. You will work closely with engineering teams to optimize performance, enhance observability, and prevent incidents before they happen.

If you love solving complex infrastructure challenges and building tools that empower engineers, this role is for you!

What Will You Do?
As a Senior DevOps Engineer , you will:

Design, build, and maintain a highly available, scalable, and resilient production infrastructure handling millions of requests per second.
Manage and optimize tens of AWS accounts in a multi-account cloud environment.
Developing AI-driven automation frameworks and tools that more than 400 R&D engineers use while enhancing system reliability and engineering efficiency.
Design, implement, and support the LLM and agentic workflow infrastructure, ensuring its scalability and reliability.
Manage thousands of servers and containers, ensuring seamless infrastructure operations.
Improve and maintain our logging, monitoring, and alerting stacks for enhanced observability.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Collaborate with engineering teams to optimize performance, reduce latency, and improve deployment processes.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We are looking for a DevOps Engineer to join our engineering team. The ideal candidate has strong hands-on experience with cloud-native infrastructure, a GitOps mindset, and the ability to independently research and learn new tools and techniques in a fast-moving, large-scale Kubernetes environment.
Responsibilities
Design, operate, and troubleshoot Kubernetes clusters (EKS/AKS) at scale
Manage application delivery and infrastructure using GitOps tools (ArgoCD/Flux)
Build and maintain Helm charts and Kustomize overlays for multi-environment deployments
Provision and manage cloud infrastructure using Crossplane and/or Terraform
Own and optimize CI/CD pipelines (GitHub Actions, GitLab CI) for build, test, and deployment workflows
Maintain and extend observability stacks (Prometheus, Grafana, alerting rules, dashboards)
Write automation scripts and tooling in Python, Go, or Bash to streamline operations
Support AWS infrastructure across multiple accounts/regions (networking, IAM, compute, storage)
Participate in on-call rotation, troubleshoot production incidents, and drive root-cause analysis
Collaborate with platform, security, and application engineering teams on infrastructure design and reliability improvements.

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

We are seeking an experienced and highly motivated Senior DevOps Engineer to join our engineering and DevOps team. As a Senior DevOps Engineer, you will be the architect of our infrastructure, ensuring that platform is scalable, resilient, and secure. This is a hands-on role where you will bridge the gap between development and operations, automating our deployment pipelines and managing our cloud-native ecosystem. This is an incredible opportunity to shape the foundational infrastructure of a high-growth data company.

What You'll Do

Design, implement, and manage our cloud infrastructure using tools like Terraform, ensuring environment consistency and scalability.

CI/CD Automation: Take full ownership of our deployment pipelines, optimizing for speed, reliability, and developer productivity.

Cloud Orchestration: Manage and scale our Kubernetes (K8s) clusters on AWS, ensuring high availability and efficient resource utilization.

Observability & Monitoring: Implement and maintain robust monitoring, logging, and alerting systems to ensure platform health and rapid incident response.

Security & Compliance: Drive security best practices across the infrastructure, including IAM management, network security, and vulnerability scanning.

Collaborate: Work closely with software engineers to optimize application performance, containerization strategies, and database reliability.

We are looking for an experienced SRE Team Lead to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will lead a team of site reliability engineers, own the engineering roadmap for monitoring and automation, and act as a key liaison between development, operations, and platform teams. You bring at least 3-4 years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.


What will you do?

Leadership & Team Management

Lead, mentor, and grow a team of SREs, providing technical direction, career development guidance, and day-to-day management.

Own the team roadmap for reliability, observability, and automation initiatives - prioritizing work, removing blockers, and driving delivery.

Conduct regular 1:1s, performance reviews, and hiring processes to build and sustain a high-performing team.

Foster a culture of operational excellence, blameless post-mortems, and continuous improvement.

Act as an escalation point for complex incidents and reliability issues, leading post-incident reviews and ensuring follow-through on action items.


Automation & Infrastructure

Design, develop, and maintain automation tools to support infrastructure and operations teams at scale.

Manage pipelines and infrastructure workflows using Jenkins, Ansible, Python, and Bash.

Drive the adoption of infrastructure-as-code practices across the organization.

Collaborate with system engineers to improve scalability, performance, and fault tolerance of critical systems.


Monitoring & Observability

Build and extend monitoring and alerting systems using Grafana, the ELK (Elastic) stack, Zabbix, and custom scripts.

Implement and enforce observability best practices to ensure full visibility into systems, applications, and infrastructure.

Define and track SLIs, SLOs, and error budgets across key services.

Partner with development teams to embed observability earlier in the software development lifecycle.


Database & Platform Support

Support monitoring and infrastructure integration for databases including MongoDB and PostgreSQL.

Maintain documentation and champion knowledge sharing around automation, monitoring, and reliability practices.

Were looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows.

You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making ML reliable, fast, cost-efficient, and production-ready.

This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up.

What Youll Do

Build & Scale ML Pipelines
Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments.
Establish LLM-Focused CI/CD
Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment.
Optimize Runtime & Inference
Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability.
Own ML Infrastructure
Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
Operational Excellence
Monitor and optimize production models for performance, cost efficiency, availability, and observability.