דרושים » AI » senior hpc AI Engineer

We are at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment - you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.


What you'll be doing:
Build agentic workflows - loops, graphs, and multi-step pipelines - that carry real hardware network simulation and analysis work end to end.
Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain.
Work closely with network architects to understand their workflows and translate them into agent workflows they use daily.
Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency.
Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable.
Build observability across agent runs: what the agent did, where it failed, and why.
Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries.
Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling.

we have been defining computer graphics, pc gaming, and accelerated computing for more than 25 years. with an outstanding legacy of innovation, driven by phenomenal technology and extraordinary people, we are looking for a distinguished engineer to help shape the future of ai infrastructure. as part of our advanced development and research efforts, you will drive technical vision and innovation across the ai software stack, spanning gpu computing, rdma, nvlink, Storage, and large-scale distributed systems. you will research next-generation system designs, influence product and platform direction, and help define how massive-scale ai environments are built, optimized, and operated through hardware-software co-design.
what you'll be doing:
research, define, and drive co-design solutions across ai software stacks involving gpu computing, rdma networking, nvlink interconnects, Storage, and large-scale distributed infrastructure
lead deep technical investigations and proof-of-concept development in areas related to distributed ai, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design
work closely with multiple teams across the company to advance next-generation ai infrastructure technologies and influence cross-stack co-design decisions
analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and Storage layers to improve performance, scalability, and efficiency
guide the design of environments that support massive-scale ai training and inference workloads in production
 we want to hear from you!
we are committed to fostering a diverse work environment and proud to be an equal opportunity employer. as we highly value diversity in our current and future employees, we do not discriminate, including in our hiring and promotion practices, on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

We're looking for an AI Engineer to join our team. As an AI Engineer, youll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO
Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

We are looking for a talented AI Solutions Engineer to join our innovative AI team. The team develops advanced AI platforms and applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will have the opportunity to shape how AI transforms our products and internal processes worldwide. Your responsibilities will include implementing state-of-the-art AI technologies, developing all aspects of the project - AI, code, data preparation, evaluation, and deployment. We are looking for a motivated teammate who thrives on solving complex problems with AI and continuously explores emerging techniques in this rapidly evolving field.

What you'll be doing:

Design and implement Agentic platforms and workflows to simplify the agentic experience across the company.

End-to-end solutions Implementation to increase the organization quality and productivity.

Develop AI solutions that integrate seamlessly with existing products and workflows.

Build evaluation frameworks to measure and improve AI system performance.

Collaborate with cross-functional teams to identify and implement AI opportunities.

Collect and prepare data from multiple large scale sources for AI training and inference.

As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power our companys conversational products.
Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions.
In this role, you will:
Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices.
Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency.
LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows.
Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models.
Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools.
Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across our platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose our capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how we evolve from AI-enhanced internal tools to customer-facing AI products.

This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.

This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.

What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server).
Take models from research and turn them into production-ready, reliable components deployed on vessels.
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing.
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination.
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization.
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew).
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating.
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems.
Define and maintain clear interfaces between research code and production systems.
Work closely with research and backend teams to integrate new models into production systems.
Continuously improve system efficiency and reliability under hardware and runtime constraints.

We are seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.

Your Career:
The Cortex Content team powers Palo Alto Networks security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers.
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.