Software Engineer, AI Platform Research High Performance Computing (HPC)

Description

The team builds and runs cloud-hosted high performance computing environments for AI research on the company's AI Health & Life Sciences (HLS) platform, covering development, testing, and production. The goal is systems that stay available, tolerate faults, and scale.

As a senior software engineer, you will also design, build, and strengthen security solutions across the organization, in line with the company's global security, compliance, and privacy programs.

Responsibilities

• Work with engineering and architecture teams to design and build applications that manage the HLS AI research platforms, extending automation, configuration management, scalable software, and infrastructure services.
• Partner with divisions that support HLS research platforms in large-scale, cloud-centric environments, and help keep improving the security posture of the infrastructure.
• Create and adopt new tools and processes that automate configuration, deployment, monitoring, and day-to-day operations, following cloud DevOps practices.
• Build and maintain complete application stacks, from the operating system up through custom applications, running on cloud computing environments.
• Advise internal clients on security topics such as cloud architecture, hardening, monitoring, incident detection and response, and closing gaps against critical controls.
• Secure and maintain the products, tools, and processes you own.
• Find and fix misalignments in priorities between service teams, and share information with partners and stakeholders early and in a structured way so issues get resolved and goals are met.

Requirements

• A bachelor's degree in computer science or a related technical field, plus 4+ years of technical engineering experience coding in languages such as C, C++, Java, JavaScript, or Python, or equivalent experience.
• You must be able to pass company, customer, and/or government security screening, including the specialized screenings that apply to this role.
• Preferred: A bachelor's degree in computer science, information technology, mechanical, electrical, or aerospace engineering, data science, cybersecurity, or a related field.
• Preferred: 6+ years of technical experience in software, network, service, or systems engineering, or in industrial controls, or equivalent experience designing complex distributed IT or research compute systems, such as cloud, distributed, or high-performance computing systems.
• Preferred: Experience designing and building AI research application environments on a major cloud provider, including big data analytics, scale-out HPC and AI workloads, and GPU-based machine learning and deep learning.
• Preferred: Skill with Azure-native IaaS and SaaS orchestration and configuration automation frameworks.
• Preferred: Proficiency in Linux system administration, SaaS development, containerized applications, and automation tools.
• Preferred: Ability to teach others on technical and procedural topics.
• Preferred: Experience securing environments on one or more major cloud providers to an industry certification standard, such as PCI or HITRUST.
• Preferred: Experience with DevOps tools such as Azure DevOps, GitHub, or Bitbucket in a cloud-centric setting.
• Preferred: A team player who performs well and adapts to a dynamic environment, identifying, defining, recommending, and building the best service solutions.

Conditions

This is the Software Engineering IC4 level.

The typical base pay range across the U.S. is USD $119,800 to $234,700 per year.

In the San Francisco Bay Area and the New York City metropolitan area, the base pay range is USD $160,200 to $261,000 per year.

The role stays open for at least 5 days, and applications are accepted until it is filled.

Benefits

• Some roles may be eligible for benefits and other compensation.