דרושים » תוכנה » Senior Lead Infrastructure Engineer

We are a dynamic and innovative global organization seeking a highly skilled DevOps and Linux Administrator to join our IT team. You will play a key role in managing and optimizing enterprise Linux systems across our global operations while supporting modern infrastructure, development workflows, and automation. This role is ideal for someone who thrives in a fast-paced, evolving environment and is eager to expand their skillset into the realms of DevOps, SecOps, and cloud-native technologies.
What Youll Do:
Administer and maintain RHEL, Ubuntu, and Oracle Linux systems across enterprise environments.
Configure, deploy, and upgrade Linux workstations and servers, ensuring optimal performance, reliability, and security.
Implement and enforce organizational policies related to security and compliance, particularly within the context of Linux systems.
Provide Linux support for Kubernetes, Docker, and other containerized environments, enabling seamless cloud-native development and CI/CD pipelines.
Automate administrative processes using scripting and internal tools, contributing to greater operational efficiency.
Implement and manage DevOps practices, including infrastructure-as-code (IAC) and continuous integration/deployment.
Work with configuration management tools such as Puppet, Ansible, and others to streamline server provisioning, software deployment, and system configurations.
Oversee the integration of Linux systems with enterprise-level Networking solutions, including Active Directory and identity management frameworks.
Manage the security of systems through advanced configuration, applying best practices from CIS Benchmarks, and actively ensuring systems comply with industry standards.
Collaborate with the SecOps team to implement security policies, hardening techniques, and continuous security monitoring.
Troubleshoot, resolve, and perform root cause analysis on system-related issues while ensuring minimal downtime and optimal system performance.

Modality Cloud AWS Engineer Cloud Infrastructure & Operations — Hands-On Role About Us Modality , part of the We-Ankor group , is a leading provider of AWS cloud solutions, dedicated to helping businesses transform and thrive in the digital age. About the Job We are looking for a hands-on, senior AWS engineer to own the day-to-day operation and delivery of customer cloud environments. This is an execution-first, individual-contributor role — you will be the one fixing things, building things, and keeping production running. The role includes on-call rotation for production incidents Key Responsibilities • Handle customer tickets: AWS administration, Linux/Windows servers, networking, storage, and security • Monitor, troubleshoot, and optimize production environments end-to-end • Implement cloud infrastructure projects independently, from design to handover • Write scripts and IaC to automate operational tasks • Participate in on-call rotation for urgent production incidents • Document procedures and runbooks; grow into a technical leadership role over time

As a Senior SRE Engineer, you will be a key player in ensuring the reliability, scalability, and performance of our critical IT infrastructure. You will leverage SRE principles and an automation-first mindset to build and maintain resilient hybrid cloud environments. This role is ideal for a candidate who thrives in a fast-paced, innovative setting and is passionate about solving complex challenges with cutting-edge technology.
Key Responsibilities
Provision, configure, and support resilient hybrid cloud deployment architectures using an Infrastructure-as-Code framework.
Proactively collaborate with development teams to ensure new applications are production-ready, scalable, and reliable from inception.
Develop and maintain tools and frameworks to automate operational tasks, including deployment, monitoring, and recovery.
Conduct thorough root cause analysis of production issues and implement preventative measures to improve system resilience, demonstrating strong problem-solving skills.
Manage CI/CD platforms, Linux infrastructure, and contribute to capacity planning and operational runbooks.
Design and implement proactive service monitoring, alerting, and trend analysis to maintain service availability and performance SLAs.
Participate in an on-call rotation to support critical applications and services, responding to and resolving incidents efficiently.
Contribute to comprehensive documentation related to infrastructure design, deployment, and operational procedures.

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 looking for a hands-on, senior AWS engineer to own the day-to-day operation and delivery of customer cloud environments. This is an execution-first, individual-contributor role - you will be the one fixing things, building things, and keeping production running. The role includes on-call rotation for production incidents
Key Responsibilities
Handle customer tickets: AWS administration, Linux/Windows servers, networking, storage, and security
Monitor, troubleshoot, and optimize production environments end-to-end
Implement cloud infrastructure projects independently, from design to handover
Write scripts and IaC to automate operational tasks
Participate in on-call rotation for urgent production incidents
Document procedures and runbooks; grow into a technical leadership role over time.

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.

abra is seeking for a Senior ML Platform Engineer . We're looking for a hands-on Senior ML Platform Engineer (MLOps) to build and maintain the infrastructure that powers secure, production-grade AI in an air-gapped environment. In this role, you'll develop and optimize ML pipelines, model serving, experiment tracking, model registries, vector databases (RAG), dataset versioning, and GPU orchestration. You'll work closely with AI developers, data scientists, and software engineers to deliver scalable, secure, and reliable AI solution

As a Senior DevOps Engineer , youll play a critical role in scaling and evolving our infrastructure as we grow. Youll work alongside experienced engineers to drive automation, optimize cloud operations, and ensure our systems are secure, resilient, and high-performing. This role is perfect for a hands-on engineer who thrives in fast-paced environments and wants to shape infrastructure practices at a product-focused security startup.



What Youll Do

Own and Evolve Infrastructure: Design, deploy, and operate infrastructure on AWS using Kubernetes to orchestrate containerized services.
Build Tools and Automate Everything: Streamline internal workflows with smart tooling, configuration management, and monitoring systems.
Lead CI/CD Improvements: Define and refine deployment pipelines to support rapid, reliable releases and cross-team agility.
Strengthen Edge Security: Manage WAFs, gateways, and load balancers to balance strong protection with great user experience.
Drive Reliability: Lead incident detection, troubleshooting, and automated recovery-improving uptime and system robustness continuously.

We are looking for a highly motivated and experienced Sr. Principal DevOps Engineer to design, build, and maintain scalable, secure, and highly available cloud infrastructure for our next-generation products.
The role drives DevOps activities across the engineering organization, with a strong focus on automation, CI/CD optimization, infrastructure as code, and the use of modern AI tools to improve development efficiency, reliability, and the software delivery lifecycle.
What you'll do:
Design, implement, and maintain scalable, secure, and highly available cloud infrastructure (e.g., AWS, Azure, GCP)
Develop and optimize CI/CD pipelines to improve deployment speed and quality
Monitor system performance, troubleshoot issues, and ensure high uptime and reliability
Automate provisioning, configuration management, and monitoring using tools like Terraform, Ansible, or similar
Collaborate with software engineers to understand and support their infrastructure needs
Define and enforce best practices for DevOps, infrastructure as code, security, and observability
Lead AI initiatives within the engineering group by leveraging AI-driven tools and integrating them into the CI/CD pipeline to enhance code quality and optimize the software development lifecycle