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we are looking for a Senior Software Engineer (DevOps).
As a DS DevOps software engineer, responsibilities include creating services to accelerate, secure, and automate DS Software Development Life Cycle processes. Tasks involve working with cloud environments, integrating open-source solutions, and -developed systems. Engagement spans cloud provisioning, network connectivity, Kubernetes deployment, performance, availability, and security. This role offers exposure to innovative technologies, global collaboration, and shaping company-wide processes and solutions.
As a DevOps, you will be responsible for:
Provisioning Cloud resources using Terraform/OpenTofu and implementing secure Kubernetes services.
Deploying, monitoring, and logging Kubernetes workloads using GitOps tools such as ArgoCD, Jenkins, Grafana, Prometheus
Planning and building highly available services and disaster recovery architecture frameworks
Cooperating with engineering support to troubleshoot complex problems across different specializations
Working through all software release stages in both development and production environments

we are looking for a R&D Architect Director.
What youll do:
Drive new technologies and frameworks - extending capacity & effectiveness of teams, capacity & scalability of the product - for both server and client side
Be involved in all key technology and methodological aspects of development and testing
Take an active role and lead key product enhancements, per product-management and stakeholders requirements, and select the right development solutions to address the requirements in terms of functionality, reliability, testability, and scalability
Be involved in business needs and operational flows to come up with the right technology solutions
Mentor and lead R&D teams in design reviews, coding standards, and architectural designs
Drive AI adoption across R&D - both as a development accelerator (coding tools, agents, MCPs) and as a capability embedded in the product

Were looking for a Team Leader who is a tech-enthusiast with a drive for excellence, and an out-of-the-box mindset to satisfy business needs in a complex payment solution environment.
What youll do:
Collaborate closely with Product, Design/UX, DevOps, and other R&D teams
Lead an autonomous team of software engineers who are working closely with product management for achieving business goals
Put special focus on developing the team
Provide technical authority to your team by demonstrating a hands-on leadership style
Be responsible for the overall design, development, architecture, code quality, and production environment deployment of your team

We are looking for a software engineer with strong backend skills, a product mindset, and the curiosity to bring LLM-powered agents into the toolchains and Linux environments where chips are actually designed. Success in this role means owning the agentic infrastructure end-to-end: from the platform our agents run on, to the integrations that let them safely act inside our customers' existing flows.
Description
You will join a growing team of ML and software engineers building GenAI solutions for chip design teams. In this role, you will:

* Architect, build, and operate the agentic infrastructure our team relies on:including LLM orchestration, tool-calling layers, multi-agent workflows, and the services that host them.
* Design and implement software solutions for chip design engineers, translating their workflows into reliable, automated agent-driven systems.
* Integrate our agents and services with existing Linux-based environments, in-house tools developed by the team, and third-party EDA tools.
* Manage agentic and ML workflows in production to ensure performance, high availability, and resource efficiency.
* Deploy and maintain production services, with proactive monitoring to catch quality and infrastructure regressions before they reach users.
* Build automated evaluation frameworks to measure retrieval quality, agent execution, and LLM output accuracy across releases.
* Partner with CAD teams to integrate pipelines and agents into CI/CD, ensuring reliable deployments and safe rollbacks.
* Implement access controls, authentication, and secret-handling practices appropriate for working with sensitive design data.
* Collaborate closely with ML engineers, researchers, and our customer teams.

We are looking for an engineer who can take ownership of a solution from understanding the business problem through production delivery and continuous improvement.
AI-assisted development tools are a core part of how you work. You use them daily, critically, and effectively to improve the quality and speed of software delivery.
You will report to a Domain Architect and work closely with senior engineering, product, and business leaders on AI initiatives and other high-impact challenges.
You will contribute across the full lifecycle: problem definition, solution design, implementation, evaluation, deployment, monitoring, and production support.
What youll do:
Own the full loop - understand the problem, define the solution, architect it, ship it, monitor it. No one hands you a spec
Build with AI as your primary tool - Claude Code, Cursor, whatever gives the most leverage; do in a day what used to take a team a week
Co-design with stakeholders and the business - decision logic, risk thresholds, success metrics
Build the evaluation harness before you ship - if you cant measure it, its not done
Own production from day one - monitoring, alerting, observability; youre on call for what you build
Raise the bar - in design reviews, in code, and in how the team works

We are looking for a talented software engineer with a passion for security to help build innovative edge-to-cloud security solutions for our next-generation devices and platforms.

You will contribute to and lead the development of core product features, from understanding system and product requirements and defining feature behavior, through architecture, design, and implementation, to delivering high-quality, secure services and endpoint components.

You will work across the stack, spanning firmware, hardware, operating systems, and cloud-connected security solutions, helping build the trusted security foundations of next-generation devices. You will collaborate with silicon partners, security experts, and engineering teams across us to deliver innovative, end-to-end security capabilities. The role offers significant technical ownership, opportunities to drive innovation, and continuous growth at every stage of your career.

AI is a core part of how we engineer. Our team has broad access to advanced AI capabilities, including unrestricted usage with no token limits, enabling engineers to fully integrate AI into their daily workflow. We actively use AI to accelerate design, coding, debugging, security research, testing, and documentation. We also empower engineers to go beyond personal productivity by building AI-powered tools and agents that improve how the entire team works and delivers value.

Join us in pushing the boundaries of security engineering. From silicon and firmware to operating systems and cloud-connected services, you'll help build trusted foundations that secure our future devices and experiences on a global scale.


Responsibilities

Partner with product, system, cloud, firmware, hardware, and security engineering teams to design and deliver innovative security solutions.

Contribute to and lead the design, implementation, integration, testing, and delivery of core security features spanning firmware, operating systems, endpoint software, and cloud-connected services.

Develop and integrate secure, reliable, scalable, and maintainable software and services using industry best practices and our high security and engineering standards.

Apply secure engineering practices, including threat modeling, secure design reviews, code reviews, mitigation planning, vulnerability response, and security validation.

Define technical requirements, architecture, dependencies, engineering priorities, and delivery plans in a complex cross-team environment.

Work closely with hardware, firmware, operating system, Windows internals, cloud, and security engineers to characterize solutions, define interfaces, and optimize security, reliability, and performance.

Drive features from inception through production, including quality, observability, deployment, monitoring, incident readiness, and continuous improvement.

Leverage advanced AI capabilities to accelerate engineering workflows and build AI-powered tools and agents that improve team productivity and product quality.

Continuously learn emerging security technologies and attack techniques, share knowledge with the team, and mentor peers as your experience grows.

The WSSI (Windows Silicon System Integration) team is looking for an experienced Data Science Manager to lead a team developing production-oriented AI solutions across computer vision and efficient small language models, helping bring advanced models to Windows products under real-world edge-device constraints.

This role offers a meaningful leadership opportunity: managing a diverse team that includes researchers, MLOps engineers, and data management experts, while shaping the teams technical direction and influencing product directions in close partnership with product and system engineering teams, all within a culture that values inclusion, collaboration, continuous learning, and individual growth.

The teams primary focus is developing state-of-the-art computer vision solutions that can run efficiently under real-world edge-device constraints, including model size, latency, power, and deployment efficiency. In parallel, the team explores similar optimization opportunities for SLMs, enabling advanced AI models to run more efficiently across Windows products.

In this role, you will help turn applied research into production-quality AI experiences, collaborate closely with product, system engineering, software, and silicon teams, and create impact for millions of customers.

Responsibilities

Lead, grow, and develop a diverse data science team that includes researchers, MLOps engineers, and data management experts, while fostering a culture of technical excellence, collaboration, ownership, and continuous learning.

Define and drive the teams technical roadmap in close partnership with product and system engineering teams.

Guide the development of production-oriented AI solutions from research exploration through production deployment, with a strong focus on quality, scalability, reliability, and measurable customer impact.

Drive model efficiency and deployment readiness for constrained environments, ensuring AI solutions meet real-world requirements for performance, latency, footprint, and resource usage.

Mentor team members, create clarity, set priorities, and help the team deliver high-impact results in a dynamic and evolving environment.