דרושים » תוכנה » Principal DevOps Engineer - AI Platforms (Cortex)

We are looking for an experienced SRE Engineer to drive the reliability, observability, and automation practices across our private cloud infrastructure and operations. In this role, you will be in 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 4+ years of hands-on people management experience and a deep technical background in SRE or DevOps disciplines.

What will you do?

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 Full Stack Engineer who enjoys building end-to-end systems in fast-moving environments. Youll work across backend services, frontend applications, and AI-integrated workflows to shape the foundation of our companys AI-powered platform.
The AI Application Foundation team is responsible for the core platform powering our companys next-generation AI applications and agentic systems. We build the infrastructure, developer tooling, orchestration layers, and user-facing experiences that transform advanced AI capabilities into production-grade cybersecurity products.
If you enjoy owning features from architecture to production, care deeply about developer and user experience, and want to work on meaningful AI infrastructure at scale- this role is for you.
Responsibilities
Design and build full-stack applications powering AI-driven cybersecurity workflows
Develop scalable backend services, APIs, and orchestration layers for applications and agent systems
Build intuitive frontend experiences for complex workflows, data exploration, and operational tooling
Collaborate with AI and platform engineers to integrate LLMs, retrieval systems, and agent capabilities into production applications
Own features end-to-end, from technical design and implementation to deployment, monitoring, and ongoing improvement
Improve platform reliability, observability, and performance across frontend and backend systems
Contribute to engineering standards, architecture reviews, testing practices, and CI/CD workflows
Work closely with Product and Design teams to rapidly iterate on new AI product experiences.

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.

Grip Security is looking for a Senior Data Platform Engineer to join our community!
We are a fast-growing startup in the software-as-a-service and AI Security Industry. We provide innovative solutions to securing the whole organization-to-SaaS surface. (More details: https://grip.security)
Using the newest technologies, we're working on solving a huge problem all enterprises face today - to govern the accessibility of all their employees to all 3rd party vendors (GitHub, SendGrid, Atlassian, and thousands more!), and ensure there is no leftover/unwanted access to any of the organization's SaaS and AI assets. The SaaS and AI security field is complex and challenging; therefore, we're looking for super-talented people, who are not afraid of technical challenges and breaking down barriers to achieve good solutions.
The job
As a Senior Data Platform Engineer, you will play a key role in building and evolving Grips modern data platform - the infrastructure that powers product features and analytics across the company.
You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.
Responsibilities:
Design, build and operate a cloud-native modern data platform.
Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
Improve developer experience and platform usability through tooling and automation.
Lead and support large-scale data migrations and architectural improvements.
Drive best practices around infrastructure, CI/CD, testing, and system design.
Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.

As a Senior AI Engineer in the global CTO group, you will play a central role in building the next generation of AI-powered security capabilities across our product portfolio. This role is focused on rapid prototyping, experimentation, and innovation, turning emerging ideas into working product features that can scale across multiple products and technology stacks.

You will design and build AI-driven systems end-to-end, from agent-based workflows and model integrations to backend services, data pipelines, and product-facing capabilities. You will work closely with product, engineering, and research teams across the company to explore new use cases, validate ideas quickly, and bring impactful AI features into production.

This role is ideal for an experienced AI engineer who enjoys moving fast, working across boundaries, and building real production systems, not just experiments. Your work will directly influence how AI is embedded across our platforms and how customers experience secure AI at enterprise scale.

Required Al Infrastructure & Reliability Engineer
What this role is really about
Youll join a 3-person platform team within our Business Technology group -owning the internal infrastructure that our AI platform and its users depend on. This isnt a product engineering role, and it isnt ticket work or babysitting pipelines someone else built. Youre building and operating the internal foundation that the company runs on. The work covers the full stack of platform engineering: core cloud infrastructure (AWS, Kubernetes, IaC), CI/CD pipelines, AI-driven infrastructure components, and the SRE and observability practice that keeps it all honest -metrics, alerting, incident response, and reliability standards. As our AI capabilities grow, so does the complexity underneath them, and staying ahead of that is central to the role. If you treat infrastructure as a product -reusable, automated, observable, and built to last -this is your kind of role.
Job responsibilities
DevOps & AI-Driven Infrastructure - own CI/CD, deployment processes, and release reliability. Build and operate cloud infrastructure that is automated, intelligent, and continuously self-improving - not just managed.
Design and build our Terraform repository and IaC pipeline from scratch -AI-assisted generation, drift detection, and policy enforcement built in.
Build AI-driven GitHub Actions pipelines -automated code review, risk assessment, and intelligent deployment decisions.
Manage Kubernetes workloads across AWS accounts -zero downtime, fully automated, nothing left behind.
Embed AI into the operational layer -proactive drift detection, automated remediation, and intelligent scaling toward a self-healing runtime.
Reliability & SRE -improve uptime, resilience, and incident response.
Define and enforce SLOs/SLIs, error budgets, and on-call practices.
Lead incident response, postmortems, and systemic reliability improvements.
Own AI-specific reliability: model latency SLOs, token quota monitoring, rate limit handling, fallback and retry strategies, and cost-per-request alerting.
Observability & Telemetry - increase visibility, reduce noise, improve troubleshooting.
Establish and continuously evolve the observability stack: metrics, logs, distributed tracing, and alerting tuned for both application and AI workloads.
AI / LLM Operations- bringing AI systems to production and operating them at scale, with a focus on reliability, performance, and trust.
Own the AI infrastructure layer: rate limits, quota management, latency SLOs, and fallback strategies (retries, circuit breakers).
Operate LLM APIs in production with resilience and cost attribution per team/model.

We're looking for a Software Engineer with strong backend and cloud expertise to join our AI team. You'll design and build backend systems that integrate Generative AI capabilities, contributing across the stack from API development to cloud deployment.
This role is ideal for someone who thinks in systems, loves solving complex problems, and can go deep into implementation details while keeping the big picture in mind. You'll work closely with our team lead on architectural decisions and take ownership of project delivery.
Key Responsibilities
Systems Design & Development
Design and build complete backend systems APIs, databases, queues, authentication, and integrations
Develop Python services with strong focus on code quality, performance, and reliability
Design solutions that scale across different client environments (cloud and on-prem)
AI Integration
Integrate LLMs (Multi Agents Systems) and GenAI capabilities into production systems
Build orchestration layers and workflows that combine AI with traditional backend logic
Optimize AI system performance, cost, and reliability
Cloud & Infrastructure
Deploy and manage systems across major cloud platforms (GCP, Azure, AWS)
Work with cloud-native services, databases, and infrastructure tools
work with production systems, monitoring, and operational health
Collaboration & Delivery
Communicate with client development teams, DevOps, and business stakeholders
Guide frontend developers on API contracts and integration requirements
Contribute to technical decisions and solution design within the team
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance.

Were looking for a DevOps Architect to help shape the infrastructure strategy behind our Revenue AI platform. This role sits at the center of our engineering ecosystem, driving architectural direction, improving operational excellence, and enabling teams to scale with confidence. Youll work across engineering groups to identify systemic gaps, define scalable standards, and accelerate execution without becoming a delivery bottleneck.
Youll Own:
Infrastructure Strategy & Standards: Define and evolve our cloud and infrastructure architecture across Kubernetes, networking, observability, security, and data platforms. Establish clear standards and scalable best practices that enable teams to move faster with consistency and reliability.
Technical Debt & System Health Visibility: Continuously identify, prioritize, and drive resolution of cross-team technical debt, architectural gaps, and operational inefficiencies. Create organizational visibility around the most critical infrastructure challenges and opportunities.
Cross-Org Technical Leadership: Partner closely with engineering leaders and teams to influence architectural decisions, challenge assumptions, and ensure solutions are scalable, maintainable, and secure. Lead through expertise and influence, not direct ownership.
Developer Enablement & Engineering Velocity: Provide frameworks, tooling direction, and lightweight prototypes or POCs that empower teams to execute independently with higher quality and efficiency.
Critical Infrastructure Initiatives: Drive major cross-functional initiatives around reliability, scalability, security, observability, and cost optimization from identification through execution and measurable impact.
Youll Solve:
Scaling Complexity: How do we maintain simplicity, reliability, and operational clarity while supporting rapid growth and increasingly complex distributed systems.
Cross-Team Alignment: How do we create architectural consistency across independent engineering groups without slowing down innovation and execution?
Operational Excellence at Scale: How do we proactively surface and resolve systemic weaknesses before they become production issues?
Balancing Speed & Sustainability: How do we enable fast delivery today while protecting the long-term health and scalability of the platform?
AI Infrastructure Evolution: How do we build infrastructure that supports modern AI/ML workloads, GPUs, large-scale data pipelines, and future platform requirements
Youll Impact:
Platform Reliability & Scalability: Your work will directly improve the resilience, scalability, and operational maturity of our infrastructure platform.
Engineering Efficiency: By creating better standards, tooling, and architectural guidance, youll act as a force multiplier for engineering teams across the company.
Long-Term System Health: Youll help reduce operational friction, minimize technical debt, and ensure our infrastructure can support long-term business growth.
Execution Quality Across Teams: Your influence will elevate engineering quality, decision-making, and operational discipline throughout the organization.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-centric technology, representing the pinnacle of computer vision, machine learning, and generative AI within the automotive sector. With over $380M in funding and strategic partnerships with industry giants such as Toyota, Amazon, General Motors, Volvo, and Hertz, our technology is utilized in manufacturing plants, dealerships, wholesale auctions, delivery fleets, seaports, and more. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity, encourages teamwork, and strives for excellence.
We are looking for a driven, systems-minded Release Engineer to join our AI-Ops team. In this role, you will be the execution layer of our delivery pipeline—the technical gatekeeper who owns the safe, predictable deployment of software and AI models to global edge and cloud systems. You will balance high-speed deployment velocity with rock-solid operational stability. But you won't just be deploying code; you'll be acting as an internal project manager, driving our organizational roadmap by building Agentic AI tools and automating processes to scale our delivery capabilities continuously.
A day in the life and how you’ll make an impact:
* Act as the technical gatekeeper, validating and transitioning versions through strict release gates. Enforce rigorous governance and ensure strict "Definition of Done" criteria are met.
* Lead risk-mitigated rollouts across diverse global hardware environments.
* Monitor real-time deployment performance, Quality of Service (QoS), and algorithmic accuracy, making decisive, crisis-resilient calls to proceed, pause, or rollback to prevent regressions.
* Define and execute comprehensive test plans that verify cross-team dependencies. Validate that new versions meet detection accuracy requirements without degrading infrastructure.
* Triage complex production failures. Look beyond immediate issues to identify root causes using system metrics, logs, and container states, delivering actionable evidence to R&D.
* Build and integrate Agentic AI and LLM-based tools to accelerate log analysis, risk assessment, and deployment troubleshooting.
* Architect automated workflows to eliminate manual overhead and enhance system observability with robust monitors and dashboards.

We are looking for an experienced Senior DevOps Engineer to join our DevOps team in the Posture R&D Group, who is passionate about software design, development and deployment. The role goes beyond traditional DevOps - it focuses on building the infrastructure and platforms that enable AI models and autonomous agents to run in production at scale, across both cloud and on-prem environments. The job involves writing production-grade modern DevOps solutions that will be shipped to the cloud and on-prem solutions, while working with cutting-edge technologies and architectures that push the boundaries of AI-driven cybersecurity systems.
Responsibilities
Build the best solutions for our production platform, enabling high-scale, AI-driven systems and agents to operate reliably in production-scale environments
Everything as a code approach (IaC): Run our infrastructure with a wide range of technologies including Terraform, and Kubernetes
Build and maintain tools for automation, deployment, monitoring, and operations, with a strong focus on scalability, resilience, and observability of distributed system.
Troubleshoot complex issues in our development, production, and test environments, including large-scale, distributed, and AI-integrated systems
Excellent communication and people skills.