דרושים » תוכנה » Senior Principal DevOps Engineer (Cortex Cloud)

The cloud security platform empowers teams through automation and security-as-code. We are looking for a Senior DevOps Engineer to design, scale, and secure our global infrastructure while setting the standard for performance, reliability, and engineering excellence across the organization.
Your Impact
Architect, implement, and optimize scalable, highly available cloud infrastructure solutions for enterprise environments.
Take full end-to-end ownership of infrastructure initiatives, driving tasks from strategic conception, implementation, and QA, all the way through to production deployment.
Manage complex production environments and execute seamless production upgrades at scale, ensuring zero-downtime and high availability.
Drive cloud cost optimization, implementing strategies to maximize resource efficiency and reduce infrastructural overhead without compromising performance.
Champion and implement AI initiatives and Agentic solutions to continuously enhance automation, operational efficiency, and infrastructure intelligence.
Establish enterprise-grade reliability by defining and enforcing SLOs/SLIs, utilizing modern monitoring ecosystems, and leading incident response strategies.
Spearhead the integration of advanced security measures, enforcing zero-trust architectures and championing security-as-code principles.
Mentor and elevate the broader engineering team, establishing cross-departmental standards for infrastructure, deployment, and security.
Partner directly with product leadership as a domain expert and power-user, shaping the strategic direction and feature development of our cloud security platform.

We are looking for a highly skilled Senior DevOps Engineer to join our Backend Infrastructure Team within the Cortex Group. Operating at the intersection of deep platform engineering and high-scale production reliability, this high-visibility role acts as a vital bridge between our DevOps organization and the Cortex Platform team - embedded closely with dev and infrastructure groups to drive broad technical impact.
Your Impact
Production Ownership: Drive end-to-end ownership, reliability, and scaling of a high-scale production SaaS environment deployed on GCP.
Infrastructure & Automation: Design and execute Infrastructure-as-Code (Terraform) to orchestrate production and dev environments, building CI/CD pipelines (Jenkins) and automated remediation tools.
Taking part of a highly skilled team, which spans from customer facing features to databases configuration and HA & DR ownership.
Platform & Data Governance: Partner with development teams to optimize distributed platform components, backend architectures, and databases.
Cross-Organizational Leadership: Collaborate with application teams, QA, and leadership to drive technical standards, platform efficiency, cost optimizations, and cross-team processes.
Platform backend shared components and architecture
On-Call Responsibilities
Participate in an on-call rotation (including weekends and holidays) supporting mission-critical Cortex platform infrastructure.
Apply strong investigative skills to troubleshoot production issues, connect complex symptoms across distributed systems, and drive root-cause resolution.
Lead customer-facing Root Cause Analyses (RCAs), translating complex technical findings into actionable post-mortem improvements.

As the Senior DevOps Architect, you will own the architectural direction of cloud infrastructure, engineering platforms, and developer experience across our Cloud and DevEx groups.
Combining infrastructure expertise with hands-on software engineering, you will turn business and engineering needs into technical roadmaps and production solutions, including AI services and agents for internal and external-facing systems.
As part of your work you will be responsible for:
Own the technical roadmap and architecture across DevOps and DevEx, establish shared standards, and lead initiatives from design to production through hands-on implementation.
Architect scalable, secure, and resilient cloud infrastructure, covering Kubernetes, networking, infrastructure as code, and modernization.
Design shared platforms and self-service workflows that simplify development, CI/CD, deployment, and troubleshooting.
Define architectural standards for observability, availability, disaster recovery, and capacity planning.
Architect and contribute to production AI services and agents, including system integration, evaluation, security, and reliable operation.
Align priorities with R&D, Product, and Security, resolve cross-team dependencies, and mentor engineers and technical leads.

Meta is reimagining shopping on our company, Instagram, and Muse. The vision is to make every piece of media shoppable. Behind that vision is our Product Recognition and Intelligence stack. It is the tech that looks at any photo, video, and text, and knows exactly which products are in it and how they relate to other products. We are building it to work at Meta's scale. Over 3 billion distinct users every day. Billions of items power a multibillion-dollar ad business.
We are hiring a senior staff Machine Learning Engineer to lead this journey. You will tackle the hardest ML systems challenges in training, serving, and evaluation. You will set the architecture and standards that raise the bar across organizations. You will ship state-of-the-art models to production where they touch billions.
If you want to have an impact at a global scale and love building tech that actually ships, come build with us.
Software Engineer - Machine Learning (Technical Leadership) Responsibilities
Identify and solve the most complex machine learning systems problems across the organization, including model training efficiency, large-scale inference optimisation, and cross-system ML pipeline reliability
Define and own the technical architecture for critical ML infrastructure components, ensuring designs are extensible, maintainable, and capable of supporting the next generation of model development at Meta's scale
Establish engineering standards and invariants for ML systems that prevent entire categories of reliability, correctness, and performance issues across multiple teams
Drive cross-organizational technical strategy by assessing emerging ML technologies, evaluating trade-offs between competing approaches, and influencing roadmap decisions with leadership and cross-functional partners
Lead the design and delivery of org-wide ML platform initiatives, coordinating across engineering teams, research, product, and data science to align on priorities and drive execution through ambiguity
Develop new metrics and data-driven frameworks for evaluating ML system health, model quality, and infrastructure efficiency, and connecting them to organization-level goals
Mentor and coach engineers across the organization on ML system design, debugging complex models and infrastructure failures, and developing scalable solutions to recurring technical challenges
Collaborate with privacy, security, and compliance teams to design ML systems that uphold user safety, meet regulatory requirements, and set the standard for responsible AI practices within the business domain
Identify and eliminate engineering bottlenecks through improved tooling, automation, and process improvements that make ML development faster and more reliable across the organization
Contribute to recruiting efforts by building relationships with candidates who bring critical ML systems expertise, and serve as a technical reference point for evaluating engineering talent at the most senior levels.

As a DevOps Engineer, youll drive, scale, and optimize our cloud environment, focusing on resilient infrastructure, cost optimization, and automation. You'll collaborate with Security, internal interfaces, vendors, and partners to develop solutions that align with business goals. If you're an infrastructure expert with strong coding skills and a passion for cost-efficiency and communication, this role is for you.
In your day-to-day, you will:
Design, implement, and maintain scalable, highly available cloud infrastructure with a focus on resilience, automation, and security
Analyze cloud expenditure, design cost-effective architectures, and drive FinOps strategies to optimize operational expenses
Develop tools, automations, and features driven by Security team requirements to ensure strong posture and compliance
Act as a key technical focal point when engaging with vendors, external partners, and internal engineering/product stakeholders
Implement and maintain Infrastructure as Code (IaC) practices to enable seamless deployment processes
Ensure full visibility into system health, performance, and operational metrics.

Your Career:
Palo Alto Networks is seeking a Senior or Principal Backend Engineer (we are open to hire both levels) for our Cortex engineering group, focusing on Cortex XSOAR, Cortex XSIAM, and new Cortex AI solutions. In this role, you will design and implement robust backend services for our leading-edge security orchestration, automation, and response platform. You will also contribute to creating innovative AI-based solutions, enhancing shared Cortex infrastructures. This is an exceptional opportunity for those eager to advance Cortex products with AI-driven capabilities and make a significant impact in the cybersecurity industry.
Your Impact:
Own the end-to-end backend development of features and components, from design and development to testing, deployment, and maintenance.
Proactively collaborate and exchange information with peers across different teams and disciplines to shape solutions and ensure alignment on product integrations.
Contribute to team-wide efforts including code reviews, design reviews, and architectural decisions, ensuring high-quality and maintainable code.
Apply a production-oriented approach, providing real-time mitigation and effective solutions to production issues to ensure platform stability and reliability.
Challenge curiously and positively by exploring new technologies and methodologies to enhance our backend services and AI capabilities.

We are looking for a proactive and skilled Software Infrastructure Developer with a strong Agentic AI focus to join our team. In this role, you will design and build the infrastructure, tooling, and AI-powered automation that keep our engineering systems reliable, scalable, and intelligent.

You will be responsible for embedding GenAI and agentic capabilities into our internal developer platforms and CI/CD workflows - creating frameworks, libraries, and multi-agent systems that accelerate automation, improve system stability, and unlock new levels of engineering productivity. This is a hands-on role for someone who thrives at the intersection of infrastructure engineering and applied AI.

The ideal candidate brings deep technical expertise in Python (FastAPI) and/or TypeScript, Kubernetes, CI/CD (Jenkins, GitHub Actions), containerization, and cloud infrastructure - combined with hands-on experience building LLM-powered applications, agents, MCP servers, and RAG pipelines.

What you'll be doing:
AI Platform Development: Design and build internal AI platforms, reusable SDKs, libraries, tools, and MCP servers for agentic applications.
Agentic Workflow Development: Develop single- and multi-agent workflows covering planning, tool selection, delegation, state and memory management, execution, retries, fallbacks, error recovery, and human-in-the-loop approval.
AI-Powered Infrastructure & CI/CD: Integrate AI capabilities into Kubernetes infrastructure and Jenkins/GitHub Actions pipelines to improve development, testing, deployment, and operational workflows.
AI Observability & Evaluation: Implement agent tracing, prompt and tool-call logging, latency and error monitoring, token and cost tracking, regression testing, and failure analysis.
AI Security & Governance: Apply guardrails, access controls, auditability, and governance practices to ensure agents operate safely and reliably.
End-to-End Platform Ownership: Own AI platform capabilities from architecture through production and build reusable solutions that accelerate adoption across engineering teams.
Cross-Functional Collaboration: Collaborate with engineering and business teams to identify high-impact AI opportunities and translate them into scalable technical solutions.
AI Research & Innovation: Evaluate emerging AI frameworks, models, and cloud technologies and promote their adoption where they provide measurable value.

we are seeking a highly technical, hands-on Software Engineering Team Lead for our Cortex XSIAM group. You will manage a high-performing team of 3 senior and principal engineers to build a complex, long-term AI agent project. This role requires a highly adaptable "orchestrator" - someone who can seamlessly drive cross-platform architecture, collaborate with multiple Product Managers and infrastructure teams, and remain deeply hands-on with the codebase.
Your Impact:
Lead & Code: Manage a senior team while remaining heavily involved in writing, reviewing, and optimizing complex backend code.
Architectural Leadership: Drive high-level design and cross-platform architecture across multiple repositories and products.
Cross-Functional Collaboration: Act as a central focal point, aligning with various PMs and infrastructure teams to shape and deliver AI-driven solutions.
End-to-End Ownership: Own the full development lifecycle, from system design to production stability and real-time issue mitigation.