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The AI software team is building solutions that enable the latest AI models and workflows to run efficiently on our unique hardware architecture-unlocking a new level of performance.

Our team is looking for a skilled professional to join the AI software group. In this role, you will focus on our AI kernel compilers, ensuring our hardware delivers peak optimization for sophisticated and custom AI kernels. You will work extensively with various kernel infrastructures, including Triton and CUDA, while collaborating closely with our AI graph compiler teams.

Responsibilities
Develop our AI kernel compilers and related components in the SW stack.
Drive the performance optimization of AI models running on our unique architecture.

Join the company Headless team, where you'll build and own products that give our company users the flexibility to create and grow their online presence in new ways.
Our team owns the product end to end - from the first interaction at the top of the funnel, through activation and conversion to premium, to the ongoing experience of our users. This means you'll work on problems that combine deep engineering challenges with product thinking and have a direct, measurable impact on key business KPIs.
You'll move between designing backend systems, solving architectural challenges, building product capabilities, and improving user experiences.
You'll have the opportunity to understand the entire product journey and influence both how we build and what we build.
We're looking for hands-on engineers who enjoy seeing the bigger picture. People who can take an ambiguous problem, understand the user and business need behind it, collaborate across disciplines, and drive a solution from idea to production and beyond.

You'll be a senior engineer on a deliberately flat, entrepreneurial team. Day to day you'll design and build agentic AI systems - agents, workflows, the orchestration layer that ties them together, and the infrastructure that makes all of it reliable at scale. This is hands-on building, not oversight.
What you'll do
Design and build agentic workflows and the AI systems behind them - agents, the orchestration layer, and the infrastructure that runs them reliably
Take significant, ambiguous areas of the system and drive them from rough idea to working capability
Help scale the platform from a first working workflow to something used across the marketing organization
Contribute to evaluation, quality, and reliability - making sure systems don't just run, but run well
Work directly with the people who'll use what we build, and translate their needs into systems.

As an xEngineer at AI Creation, you'll take on some of the most exciting engineering challenges at our company, shaping how AI becomes a core part of creating and editing stunning sites.
Take on engineering challenges to integrate AI as a first-class part of site creation and editing
Work on complex systems requiring deep technical understanding and collaboration with multiple engineering groups
Lead and own features end-to-end, from research and technical design to implementation and deployment
Collaborate closely with product managers, UX designers, and fellow engineers to deliver impactful solutions
At our company, we believe our best work happens together. Our work model is fully in person, with 5 days a week from our office. Flexibility remains a core value at our company and special requests are handled thoughtfully at the team level.

We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our company Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.

We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today.
Key Responsibilities
Develop internal AI-powered products and tools used by teams across our company to work faster and smarter.
Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams.
Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows.
Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development.
Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption.
Work hands-on with the most advanced AI development tools and shape how the company uses them.

We're looking for an AI Workflow Engineer to join our System Architecture group. This is a high-impact role where you'll design, build, and continuously improve AI-powered workflows, agents, and tools that help our architects do their best work - from system design and modeling through documentation, technical decision-making, and review.
Working from within the architecture team, you'll turn the group's real, day-to-day pain points into practical AI-assisted solutions. Your primary focus is system architecture within the software development lifecycle (SDLC), and because architecture touches everything, your work will naturally extend into adjacent stages wherever AI can add value.
Key Responsibilities:
Design and build AI-powered workflows, agents, and internal tools that support system architecture work - design, modeling, documentation, architecture decisions, and reviews.
Develop and iterate on agents within our internal framework, using agentic AI techniques to accelerate and augment architecture and engineering tasks.
Continuously improve existing workflows and tools as team needs evolve and AI capabilities advance.
Partner closely with the System Architecture team to understand real pain points and turn them into practical, AI-assisted solutions.
Measure and demonstrate the impact of the workflows you build - for example on design-cycle time, review turnaround, and the quality and completeness of architecture documentation and decision records.
Build proof-of-concept projects that show the practical value of AI in real architecture and engineering workflows.
Develop best practices, prompt engineering guidelines, and reusable patterns for AI-assisted architecture and development.
Stay current with the rapidly evolving AI tooling landscape and advise on strategic adoption.

We are seeking a senior ATE Software Engineer to design, build, and deploy our next-generation automated manufacturing test platform for advanced telecom, high-density switching, and optical networking hardware.
In this role, you will bridge the gap between R&D hardware/firmware teams and high-volume manufacturing lines. You will take ownership of ingesting, refactoring, and consolidating disparate R&D scripts, diagnostic tools, and legacy software into a single, scalable, production-grade test platform.
We expect you to leverage modern AI-assisted development tools and workflows to maximize engineering efficiency, accelerate delivery timelines, and build highly robust, self-healing test automation. You will deploy test stations across global Contract Manufacturers (EMS/ODM), actively stabilize production lines through bring-up and ramp-up, and drive continuous test maintenance and root-cause failure analysis (RCA).
Key Responsibilities
Test Platform Architecture & Software Development:
Design, develop, and productize robust, modular test software frameworks for board-level (PCBA) and system-level manufacturing testing across multiple product lines and manufacturing sites.
Codebase Unification & Refactoring:
Consolidate and standardize R&D diagnostic libraries, silicon validation scripts, and firmware tools developed across various environments (Python, C# / Visual Studio, VB, ATEasy, Linux) into a unified, maintainable test execution engine.
AI-Accelerated Development & Workflow Automation:
Actively integrate Generative AI tools and AI coding agents into your daily workflow to accelerate code conversion/refactoring, automate test case synthesis, generate edge-case validation scripts, and enhance overall codebase resilience.
Production Line Deployment & Stabilization:
Deploy test stations and fixtures to local and overseas EMS/CM production lines. Monitor, debug, and fine-tune test execution during NPI and ramp-up phases until yield, takt time, and test stability targets (CPK / First Pass Yield) are achieved.
Failure Investigation & Intelligent RCA:
Investigate complex system-level and component-level test failures. Utilize advanced log analysis, structured telemetry, and pattern recognition to drive root-cause investigations and implement preventive software/hardware fixes.
Ongoing Test Maintenance & Optimization:
Provide continuous operational Production line support and maintenance, bug fixes, software updates, and station cycle-time optimizations for active mass-production lines.
R&D Collaboration & Test Specification:
Collaborate closely with Hardware, Firmware, and Validation teams during early design phases to define test specifications, drive Design for Testability,
Documentation & Technical Reporting:
Author and maintain comprehensive testing documentation, Standard Operating Procedures (SOPs), test coverage matrices, and detailed failure analysis reports.
Manufacturing Systems Integration:
Integrate automated test sequences with CMs SFC/MES/QMS, serialized tracking, and central test log databases.
Log Analysis & Analytics Tool Development:
Design and build dedicated log parsing, data visualization, and diagnostic analytics tools to streamline complex hardware/software debugging, accelerate root-cause analysis (RCA), and drive continuous production line cycle-time and yield optimization.

We are looking for a DevOps IT Engineer to join our dynamic IT team. This role blends hands-on system administration with modern DevOps practices, focusing on building, automating, and operating scalable hybrid environments across on-prem and cloud platforms.
If you are passionate about automation, cloud infrastructure, and improving developer productivity while maintaining robust and secure enterprise systems - we want to hear from you!
Responsibilities:
Design, build, and operate scalable infrastructure across on-prem environments and cloud platforms (AWS & Azure).
Manage and evolve virtualization platforms such as VMware and KVM (Proxmox).
Implement and maintain cloud infrastructure using Infrastructure as Code (IaC) and DevOps best practices.
Own identity and access management solutions including Azure Entra ID (Azure AD), SSO, MFA, Conditional Access, and directory synchronization.
Manage enterprise endpoint solutions such as Microsoft Intune and MobileIron/IVANTI.
Automate infrastructure provisioning, configuration, monitoring, and operational workflows.
Build and maintain internal tools to improve developer experience and engineering productivity.
Ensure system reliability, performance, and cost optimization across cloud and on-prem environments.
Maintain high security standards, compliance, and operational best practices.
Collaborate closely with DevOps, R&D, Security, and IT teams to support development and production environments.
Develop and maintain clear technical documentation.

We are looking for a DevOps IT Engineer to join our dynamic IT team. This role blends hands-on system administration with modern DevOps practices, focusing on building, automating, and operating scalable hybrid environments across on-prem and cloud platforms.
If you are passionate about automation, cloud infrastructure, and improving developer productivity while maintaining robust and secure enterprise systems - we want to hear from you!
Responsibilities:
Design, build, and operate scalable infrastructure across on-prem environments and cloud platforms (AWS & Azure).
Manage and evolve virtualization platforms such as VMware and KVM (Proxmox).
Implement and maintain cloud infrastructure using Infrastructure as Code (IaC) and DevOps best practices.
Own identity and access management solutions including Azure Entra ID (Azure AD), SSO, MFA, Conditional Access, and directory synchronization.
Manage enterprise endpoint solutions such as Microsoft Intune and MobileIron/IVANTI.
Automate infrastructure provisioning, configuration, monitoring, and operational workflows.
Build and maintain internal tools to improve developer experience and engineering productivity.
Ensure system reliability, performance, and cost optimization across cloud and on-prem environments.
Maintain high security standards, compliance, and operational best practices.
Collaborate closely with DevOps, R&D, Security, and IT teams to support development and production environments.
Develop and maintain clear technical documentation.

We are seeking an exceptional software engineer with the imagination to challenge existing designs and the discipline to implement those ideas in production-quality systems.
This role requires a passion for software development, strong system design skills, and deep expertise in coding and debugging. The ideal candidate is also a natural mentor, capable of guiding and developing junior engineers.
This position is for a Principal Software Engineer with extensive experience in databases and systems algorithms for distributed data platforms (databases, replication, HA, data-traversal, deduplication), who can lead the design and implementation of large, complex initiatives end to end.

we are a leader in large-scale networking solutions for AI infrastructure and service providers. The company's disaggregated networking architecture transforms the economics of large-scale infrastructures while maximizing performance, utilization, and operational efficiency. Its high-performance AI fabric maximizes GPU utilization and accelerates deployments by optimizing the AI stack end-to-end, resulting in higher tokens-per-second and lower cost-per-token. our company's solutions power production networks for global tier-1 operators like AT&T and Comcast, and scale multi-vendor AI infrastructures at foundation model labs, NeoClouds, and enterprises.
our company's Cybersecurity business unit is building an AI-powered security platform for the world's largest service provider networks. The platform combines a cloud-native microservices backend with self-hosted LLM inference, delivered into customers' own Kubernetes environments - often air-gapped, with no data leaving their premises.
Responsibilities
Own the platform's Helm charts and make them portable across any Kubernetes distribution, including OpenShift (non-root, restricted SCCs, NetworkPolicies).
Operate the self-hosted operator stack: CloudNativePG, Strimzi, ECK, MinIO, Redis, and Temporal.
Run the Nx monorepo pipelines and drive the ArgoCD GitOps rollout.
Build zero-downtime releases using blue/green and canary deployments, expand/contract migrations, and automated rollback.
Manage autoscaling with KEDA/HPA, backup/restore for stateful services, and load-validation of stamp sizing tiers.
Provide on-call support for dev/staging environments and customer stamps.
Build and maintain observability using Grafana Alloy, OpenTelemetry, and Prometheus/Grafana - dashboards and alerts across services, Kafka, databases, and GPUs.
Improve developer experience through a shared dev cluster with local-debug traffic interception (Telepresence / mirrord), targeting sub-15-minute onboarding.

We're hiring a Quality Lead to own that. Why this role is different: you won't run a traditional QA team that tests features at the end. You'll own the quality gates inside the Machine and in production, author the monitoring skills our pods rely on, and hold independent authority to fail the Machine's output. Quality is our north star, and this role sets the bar.
THE MISSION: Make reliability, performance, and user experience a property of the system - not of individual heroics. Build and lead a Quality function (~9 people) that keeps an AI-native delivery org fast and trustworthy, and give the business confidence that what the Machine ships is safe to ship.
WHAT YOU'LL DO:
Own quality gates in the Machine - prose-driven tests (generated from requirements, not the code), adversarial / agent-checks-agent review, static analysis and code-quality remediation (e.g. SonarCloud), and CI gates that run before anything reaches a human.
Own quality in production - release verification, production testing, and ownership of change-fail and deployment-rework rates.
Author monitoring guidelines & reusable observability skills that delivery pods and the Machine consume - so monitoring is built in, not bolted on.
Own the evals that score the Machine's output for behavioral consistency and reliability - treating evaluation as a first-class engineering discipline.
Act as an independent governance voice - with the authority to block or fail output that doesn't meet the bar, partnering closely with Architecture.
Partner with the Core Platform team on the quality of customer-issue fixes and existing functionality.
Lead, coach and grow the team - quality/gate engineers, an agent-evaluation engineer, production-monitoring (SRE) and QA-infrastructure engineers.
Set the quality metrics and report them - DORA + deployment-rework rate, escaped-defect rate, review-queue depth, eval pass rates.

As a Solution Engineer, you will play a pivotal role in designing, deploying, and optimizing our companys Network Cloud AI Infrastructure solutions. This individual contributor role requires a blend of technical expertise, leadership, and hands-on experience to implement cutting-edge solutions for our customers. You will collaborate with sales engineering teams, customers, and cross-functional teams - including Product Management, Solution Architects, Engineering, and Marketing - to define technical requirements, articulate solution value, and ensure successful deployment on-site.
Key responsibilities include guiding customers through the design and deployment process, aligning technical solutions with business needs, and providing critical feedback to improve our companys product offerings. This position demands strong technical acumen, exceptional communication skills, and the ability to lead complex, high-impact projects in dynamic environments.
Responsibilities:
Design and plan rack layouts and network topologies to support customer requirements.
Perform Data Center upgrades and ensure smooth deployment of our company solutions.
Install and configure our company products, ensuring optimal performance and customer satisfaction.
Design and implement compelling Proof of Concept lab setups, run them, and collect and document the results for the field consumption
Develop and deliver HLD and LLD documentation for customer deployments.
Design and evaluate automation scripts for network operations, configuring server and switch fabrics.
Engage with sales teams and customers to ensure success with major opportunities and deployments
Introduce new products to the company sales and support teams and to company customers
Deliver technical trainings and TOIs for support/sales engineers, partners, and customers
Collaborate on product definition through customer requirement gathering and roadmap planning.