We are looking for an AI & Automation Engineer to design, build, and enable enterprise AI infrastructure and automation solutions.
This role focuses on AI architecture, workflow automation across IT and business applications, and monitoring, governance, and cost management of AI tools and agents.
You will work at the intersection of AI platforms, IT operations, and business automation, enabling scalable, secure, and cost-effective AI adoption across the organization.
Responsibilities:
Select and integrate AI tools, frameworks, and platforms aligned with enterprise IT standards.
Ensure scalability, security, reliability, and compliance of AI infrastructure.
Enable AI solutions from concept to production, including:
AI-powered IT tools
AI agents and copilots
AI services integrated into business applications
Collaborate with IT, DevOps, Security, and Business teams to deploy AI solutions smoothly.
Build reusable AI enablement patterns, templates, and best practices.
Automation of Workflows
Design and implement automation of IT and business workflows using AI and orchestration tools.
Integrate AI agents into:
IT operations (ITSM, monitoring, incident response)
Business applications and internal systems
Improve efficiency, reliability, and user experience through intelligent automation.
AI Monitoring, Usage & Financial Governance
Define and implement monitoring for AI systems, including:
Usage tracking
Performance and reliability
Model and agent behavior
Track and analyze financial usage and cost of AI tools, APIs, and platforms.
Establish governance frameworks for responsible and controlled AI usage.

We are looking for an outstanding Senior Technical instructor to join our Education Services team. In this role, you will provide advanced training on our data center, AI, and HPC platforms to customers and partners around the world. You will also contribute to developing training content, including presentation decks, hands-on manuals, and supporting materials. You will help engineers, architects, and operations teams build the skills needed to design, deploy, and operate our-powered AI data centers with confidence. As part of this, you will take part in the design of hands-on workshops and lab environments that simulate real systems and data center components, enabling learners to practice on realistic end-to-end scenarios.

What youll be doing:

Deliver in-person and remote technical training on our data center, AI, and HPC platforms for customers and partners, with up to 25% travel as needed.

Lead lab-based training sessions that walk learners through end-to-end workflows on our GPUs, DGX/GB200 systems, high-speed networking, and AI/HPC software stacks.

Collaborate with internal experts and content developers to build agendas, exercises, and demos that reflect real customer use cases and guidelines.

Serve as a subject-matter guide (SME) for a dedicated production team and learning developers. They build primary content. Partner with them on slideware, lab guides, videos, simulations, visual demos, and exercises. Ensure technical accuracy and realism.

Act as a technical ambassador for us in front of partner and customer audiences, answering inquiries, facilitating discussions, and guiding learners through fix and what-if scenarios.

We are looking for talented, highly motivated Senior Java Software Engineers to join our Cloud Analytics group. If youre passionate about building modern cloud architectures and enjoy solving complex engineering challenges, this role is for you.
You will help design and develop large‑scale, AWS‑based systems that power the global CXone cloud platform. The applications you build are deployed across multiple regions and support hundreds of enterprise customers worldwide.
How will you make an impact?
Design and implement scalable microservices using AWS technologies.
Develop high‑quality services in a Java Spring Boot environment.
Participate in the full feature lifecycle-from design to implementation.
Analyze requirements and create clear, comprehensive design documentation.
Review and refine designs with peers and stakeholders.
Collaborate closely with the team to iterate on architecture and features.
Apply agile methodologies with AI tools to deliver reliable, high-impact capabilities efficiently.

Spectrum-X is our ethernet networking solution for massively scaled AI factories. As the Spectrum-X Integration Engineering manager, you will lead a team to ensure that the solution's software features are developed, tested and delivered to meet the high standards of our customers. Do you want to help create the most exciting solutions in the world of networking today? If so, read on.

What you'll be doing:

Engaging directly with our customers to ensure we are aligned on their networking requirements.

Marshalling a cross-disciplinary team of architects, testers, customer managers, and other software teams to deliver products and features on time.

Defining and reviewing switch architectures and test plans.

Providing expertise on ethernet networking both internally and to customers.

As a Graph Compiler Software Manager, you will lead the development of next-generation graph compiler technology. This compiler is a cornerstone of AI software offering, empowering customers to optimize, map, and execute complex neural networks across architectures with extraordinary efficiency. You will lead a group of talented engineers and team leaders working across domains such as compiler optimizations, graph-level transformations, operator mapping, scheduling, and code generation. We are seeking a visionary and technically strong leader with passion for excellence and impact in one of the most fascinating areas of AI and deep learning.

Key Responsibilities:

Lead the design and implementation of innovative graph compilation flows for AI workloads, from high-level optimizations to hardware-specific backends. Build and guide a strong, innovative, and results-driven compiler team that thrives on solving complex technical challenges. Collaborate with hardware architecture, VLSI, and software framework teams worldwide to ensure seamless integration and maximum performance. Lead the end-to-end delivery of graph compiler components while meeting aggressive KPIs. Establish and execute group planning processes to ensure timely and high-quality delivery. Provide technical and managerial guidance to team leaders and engineers. Define and drive compiler optimization strategies for AI and deep learning workloads.

We are seeking a highly skilled and visionary Lead Data Scientist with deep expertise in Generative AI to lead high-impact initiatives at the frontier of AI innovation. This role requires a unique blend of advanced technical skills, domain specialization, leadership ability, and a passion for delivering real-world impact. You will guide a small team of talented data scientists and work collaboratively across engineering and product teams to design, build, and deploy intelligent, domain-specific multi-agent systems.

What will your job look like?
Lead the design of complex, domain-specialized multi-agent Generative AI systems.
Provide technical mentorship and leadership to a team of 3-4 data scientists.
Drive hands-on research and rapid prototyping in areas including LLM fine-tuning, prompt engineering, agentic workflows, and self-improving systems.
Collaborate with product managers, engineers, and domain experts to identify opportunities and deliver AI-driven features and products.
Evaluate and integrate state-of-the-art models and tools from the GenAI ecosystem, including open-source and proprietary solutions.
Translate research outcomes into actionable product features and influence AI strategy and roadmap.
Maintain high standards for scientific rigor and data integrity throughout the development lifecycle.

We are looking for an experienced Software Engineer to join our team with a focus on services and infrastructure development, while being comfortable contributing across the full software stack when required.

This role is well suited to an engineer who enjoys designing and building scalable backend services, integrating them with infrastructure platforms, and contributing to end-to-end solutions that support sophisticated engineering workflows. While some components may include frontend elements, the primary emphasis is on service architecture, APIs, data handling, and system reliability.

In this role, you will collaborate closely with engineers and partners across the organization to design, deliver, and evolve maintainable solutions that underpin GPU software engineering infrastructure. You will also contribute to technical direction, mentor others, and help shape the long-term evolution of our platforms.

Responsibilities:
Design, develop, and maintain scalable backend services using Python, Go or similar languages, with the ability to contribute to full-stack solutions where appropriate.
Take ownership of services across their lifecycle, from design and implementation through deployment and production support.
Design and evolve APIs and service interfaces that support tooling, automation, and infrastructure workflows.
Contribute to end-to-end feature development, spanning backend services, APIs, and selective frontend components where they support infrastructure use cases.
Collaborate closely with teams across tooling, automation, and infrastructure to ensure seamless service integration.
Improve system reliability, performance, and scalability through thoughtful design and continuous optimization.
Contribute to infrastructure modernization initiatives, including cloud-based and containerized deployments.
Follow and promote standard methodologies for code quality, testing, documentation, and design reviews.

We are seeking a highly motivated High-Performance System Architect to join our team of experts and help shape the future of high-performance and ML / AI computing. Our next-generation NVL systems will be at the forefront of connecting and powering the world's most advanced compute clusters, which would be used to train the most advanced AI models such as GPT and DeepSeek. As a high-performance system architect, you will have the opportunity to work on some of the most cutting-edge technology and help to drive the innovation of our next generation networks that will be used by top researchers and engineers around the world.

What youll be doing:
Define the NVL system architecture end-to-end, by internal requirements and customers requirements through all product life cycles (post/pre silicon, on deployments).
Research various of solutions to enable the next large-scale-high-performance computing clusters. The position spans over various layers from algorithms, software, firmware, and HW.
Collaborate with cross-functional teams, including other architecture teams, logic design, system software, firmware, and research teams, to ensure the successful execution of the project.

We are looking for a Principal Engineer to lead the architectural vision of the platforms core. In this role, you will be the internal technical authority responsible for building a unified, high-performance engine that processes massive telemetry streams and runs advanced predictive models, regardless of where the infrastructure resides.

What youll be doing:
Unified Architectural Vision: Lead the design of a flexible, high-scale architecture that supports both multi-tenant SaaS environments and complex on-premises deployments.
Operationalizing Predictive Models: Bridge the gap between AI research and production by architecting the framework that runs sophisticated predictive algorithms at scale, ensuring they are robust enough for mission-critical environments.
High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.
Cross-Organizational Leadership: Collaborate with networking and infrastructure teams to define the technical standards that enable the AIOps platform to integrate seamlessly with global AI infrastructure.
Technical Excellence: Drive the engineering roadmap, mentor senior staff, and serve as the final authority on architectural decisions, ensuring the platform meets the highest standards of reliability and scalability.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.