דרושים » AI » Staff Software Engineer, AI

Come join the team as a Staff Machine Learning Engineer. We are seeking a highly skilled ML engineer passionate about building a world-class platform at a high scale, specifically focused on delivering AI capabilities. You will be part of a vibrant team of AI Scientists and ML Engineers, helping to build the next generation of awesome products and experiences using cutting-edge Generative AI technology. If you love having stretch goals, challenges, and making customers incredibly happy while fostering your obsessive need for perfect code and user experience, this is the job for you.
Responsibilities
Design, implement, and enhance services at large scale, specifically focusing on improving Generative AI inference, quantization, optimization, finetuning, and evaluation.
Use your coding expertise to design and implement scalable, modular, and secure services.
Develop backend systems that support serving of LLMs and AI Agents at scale, utilizing the latest industry tools and techniques.
Work cross-functionally with product managers, AI scientists, business units, and other engineers to understand, implement, refine, and design Generative AI models.
Help automate, deliver, monitor, and improve GenAI solutions while taking end-to-end responsibilities including technical documentation and automation tests.
Interact with a variety of data sources, working closely with peers to refine features from the underlying data and build end-to-end pipelines.
Resolve defects and bugs during testing, production, and post-release patches, and participate in peer code reviews.
Explore the state-of-the-art technologies and apply them to deliver customer benefits.

we are the global leader in identity security. centered on privileged access management, we provide the most comprehensive security offering for any identity - human or machine - across business applications, distributed workforces, hybrid cloud workloads and throughout the DevOps lifecycle. the worlds leading organizations trust our company to help secure their most critical assets.
job description
as a staff engineer in the data & ai platform group, you will be a senior technical leader responsible for driving the design, implementation, and delivery of complex, high-impact features across our data and ai ecosystem. you will set engineering standards, lead cross-team initiatives, and provide hands-on technical guidance to developers working on large-scale, cloud-native distributed systems.
this role combines deep technical expertise with leadership: shaping the platforms architecture, mentoring senior engineers, and ensuring technical excellence and execution. in this role you will
lead end-to-end development of high-priority, cross-team features and initiatives in the data & ai platform. design and implement scalable, resilient, and secure distributed systems in a modern cloud environment. drive technical decision-making, influence architecture directions, and collaborate closely with product, data engineering, and ai teams. mentor developers, support their growth, and elevate engineering practices across the group. promote engineering excellence through code reviews, design reviews, and continuous improvement initiatives. evaluate new technologies and guide their adoption where appropriate. collaborate with engineers and managers across our company to align standards, share knowledge, and lead technical deep dives

Required AI Architect
Position Overview:
As the AI Architect for our SaaS Platform & Products, you will define and drive the end-to-end AI architecture that powers our cloud AI platform and product capabilities, while ensuring strong alignment with security, privacy, reliability and cost-efficiency requirements. You will partner closely with engineering leaders, product management, data science, security and operations to translate business needs into a scalable, governed and AI platform that accelerates innovation across multiple product lines.
This is a hands-on architecture role: you will set technical direction, run architectural reviews, and build prototypes to validate technology choices and de-risk delivery.
Key Responsibilities:
Own the AI Vision: Take end-to-end ownership of the AI architecture across, including our cloud AI platform, agentic AI infrastructure, and on-prem/hybrid AI deployments.
Architect an AI Platform for SaaS Products: Define reference architectures and shared building blocks (e.g., AI gateways, orchestration runtimes, memory/RAG systems, vector search, evaluation frameworks, observability, and guardrails) that can be adopted consistently across products and teams.
Cost Optimization and Scalability: Provide architectural leadership to ensure AI systems are designed for cost efficiency and scalability, actively identify and implement opportunities to optimize cloud spend (FinOps), improve utilization, and meet latency/SLO targets.
Product-Centric Collaboration: Collaborate with engineering, product, data science, security, and operations teams to translate product requirements and business needs into a strategic AI architecture that drives measurable product value.
Technology Evolution and Prototyping: Evaluate new technologies, tools, and methodologies to continuously improve our AI systems, build prototypes and proof-of-concepts to validate approaches and accelerate decision-making.
Technical Reviews, Standards and Mentorship: Lead technical design reviews and provide guidance on best practices and emerging technologies. Act as a technical authority and mentor, fostering a culture of engineering excellence and pragmatic delivery.
AI Governance, Privacy and Security: Ensure AI capabilities comply with data privacy, security, and ethical AI guidelines. Partner with security and legal stakeholders to implement governance controls and risk mitigations appropriate for regulated environments.

Join our companys Content Safety team as a Staff AI Scientist, where youll build the intelligent infrastructure that keeps our global platform secure. We're looking for a specialist to design and deploy production-grade GenAI solutions that moderate content at scale. From pioneering automated labeling workflows to securing AI-generated outputs, your work will define the safety standards for every product in the company portfolio.
Responsibilities
Architect Robust Moderation Systems: Lead the design and deployment of sophisticated, multi-modal content moderation engines to detect and mitigate abusive content across our companys diverse product ecosystem.
Drive LLM Strategy: Direct the fine-tuning and optimization of state-of-the-art Transformers and Large Language Models (LLMs), balancing high-precision accuracy with production-scale efficiency.
Pioneer Agentic Workflows: Research and integrate advanced GenAI patterns-including Retrieval-Augmented Generation (RAG) and Agentic AI-to revolutionize automated data labeling and complex classification taxonomies.
Cross-Functional Leadership: Partner closely with ML Engineers, Product Leads, and Policy Experts, to help ensure AI systems aren't only technically superior - but also ethically grounded and compliant with global safety standards.
Technical Evangelism and Research: Act as the teams North Star by staying at the bleeding edge of AI research, translating academic breakthroughs into practical, "production-first" content safety strategies.
Communication and Governance: Standardize high-quality documentation and model governance. You will translate complex technical architectures into clear, actionable insights for both executive stakeholders and technical peers.
Team Upskilling and Mentorship: Serve as a force multiplier by mentoring junior and senior scientists, conducting rigorous code/design reviews, and fostering a culture of technical excellence.

a palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere. learn more. job description
we are looking for a senior ai software engineer to join our generative ai foundation team. we build ai agents and shared infrastructure that power genai capabilities across the company, enabling product lines to adopt agentic workflows safely, reliably, and at scale.
in this role, youll be involved in the full software lifecycle - from fast-moving prototypes and pocs to production-grade, observable systems. youll collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence.
youll work hands-on with leading llms and the modern agentic ecosystem, leveraging a wide range of aws services. youll use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve our solutions through solid design, flexible implementation, strong telemetry and evaluation, and production feedback loops

- Drive technical decisions around AI evaluation frameworks, monitoring, and observability tools
- Design, build, and deploy AI-powered solutions across yad2s products and platforms
- Work hands-on with Large Language Models (LLMs), retrieval-augmented generation (RAG), embeddings, vector databases, and prompt engineering
- Develop scalable backend services that integrate AI capabilities into production
- Collaborate closely with product, data, and engineering teams to identify high-impact AI opportunities
- Lead by example: write clean, high-quality code, set best practices, and help shape the foundation of the AI team

Reuired senior software engineer
company description
A palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. Our ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description
be part of analyzing, designing and developing new features for the web interfaces and backend infrastructure for a fast growing saas enterprise product. take part in feature development from the requirement definition stage to final deliverable.
lead and own various development efforts in the group ( backend / frontend )
research platforms and frameworks in the server side, cloud and container orchestration domains, web, UI.
produce quality products that meet high security, stability and performance standards
diverse technology stack using various programming languages such as JAVA spring boot, angular 13+.
member in a highly talented cross-functional development team, built of developers, architects and QA, in an agile oriented environment
report to r&d team leader.

Required AI Platform Engineer
Position Overview:
We're assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As an AI Platfrom Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
Build advanced AI platform that operates both as a cloud SaaS and as a fully self-contained on-prem / edge deployment, designed for privacy-sensitive and security-critical environments, at the intersection of backend development, AI integration, DevOps, and open-source systems engineering.
You will be part of the core team responsible for adapting, hardening, and operating our SaaS architecture in on-prem and single-node environments (on Prem servers, laptops). Working closely with architecture and product management and play a key role in making complex AI systems deployable, reliable, and operable outside the cloud.
Key Responsibilities
Platform & Application Engineering:
Adapt cloud-native AI services to on-prem and edge deployments (single node, no managed cloud services).
Build and maintain full-stack components: Backend APIs (Python / Node.js), Lightweight UIs or internal tools when needed, Ensure services are stateless, configurable, and portable across environments.
AI & Open-Source Integration:
Integrate and operate open-source LLMs for:
RAG pipelines
Agentic workflows
Tool calling and orchestration
Work with: Embedding models, Vector databases (local and embedded modes), Analytical engines (e.g., embedded SQL / columnar systems), Optimize inference for CPU / single-GPU environments (quantization, batching, caching).
DevOps & Runtime Engineering (Strong Focus):
Package services into portable Docker containers usable in:
On-prem servers (Kubernetes)
laptop / edge devices
Implement in-process scaling strategies (worker pools, task queues, batching).
Build simple, reliable deployment and startup flows (no heavy orchestration).
Manage configuration, secrets, logging, and observability in constrained environments.
Systems & Reliability:
Design for: Offline operation, Limited resources, Predictable performance
Implement graceful degradation between: SaaS mode, On-prem server mode, Single-node / laptop device mode, Debug complex interactions across AI models, storage, and runtime systems.

a palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description:
were building foundational infrastructure to secure ai agents-including their identities, access patterns, and interactions with sensitive systems and data. this includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent and user identity tailored to the modern agent ecosystem.
as a staff engineer, youll take ownership of these critical systems, designing and implementing how agents establish identity, receive dynamic access, securely interact with sensitive systems, and leave verifiable audit trails. youll shape the long-term architecture, anticipate technical risks, and evolve systems that span both machine- and human-facing workflows.
this is a rare opportunity to combine hands-on engineering with technical leadership-writing critical code, mentoring engineers, sharing knowledge, and driving best practices-while building a platform from the ground up at the cutting edge of ai, identity, and security.
responsibilities
own and guide the technical direction of core platform domains, including agent identity, authentication, authorization, and secrets management, shaping architectures that span multiple services and teams while balancing scalability, reliability, and security. lead by example through high-impact implementation, mentoring engineers, and helping them navigate complex technical tradeoffs. proactively identify critical technical problems or gaps, and drive solutions from concept through delivery. establish and promote engineering best practices, ensuring high standards for code quality, security, and operational excellence. communicate complex technical concepts clearly to engineers, architects, product managers, and stakeholders, influencing decisions, fostering alignment, and driving cross-team collaboration. document key decisions, patterns, and practices to elevate team knowledge and ensure consistency across the platform. advocate for continuous improvement and operational efficiency, helping the team work smarter while maintaining a secure, high-quality platform.

Were looking for a highly skilled AI Engineer to join our Forensic Research Group and help shape the next generation of intelligent forensic platforms.
Youll work at the intersection of Generative AI, agentic systems, and real-world data, building advanced capabilities for both internal tools and production systems that transform how complex data is analyzed and understood.
Using state-of-the-art models and emerging AI paradigms, youll design systems that move beyond traditional pipelines into autonomous, adaptive workflows.
Youll help define the future of agentic decoding - where AI doesnt just assist, but actively reason, explore, and uncover critical evidence, impacting millions of cases worldwide.
If youre excited about building impactful AI systems and solving complex, messy problems, this role is for you.
What Youll Do:
Design and build AI-driven and agentic solutions to parse, analyze, and interpret data from forensic extractions (including mobile devices)
Develop GenAI-powered capabilities for understanding, structuring, and reasoning over unstructured data
Combine LLMs, multi-agent systems, and heuristic approaches to improve data identification, classification, and insight generation
Build autonomous and semi-autonomous pipelines that transform manual and brittle workflows into scalable, intelligent systems
Work with real-world, noisy datasets to uncover patterns, anomalies, and meaningful structures
Collaborate closely with forensic researchers and engineers to translate domain expertise into AI-native solutions
Influence system architecture, tooling, and the evolution of internal AI platforms and agent frameworks
Evaluate, fine-tune, and integrate state-of-the-art models (LLMs, multimodal models, etc.) for complex real-world problems.