As a Gaussian Software Engineer - Infrastructure, you will be responsible for leading the architecture, design, and development of the DevOps tools and infrastructure on our software products are deployed.
You will be working with other passionate and talented Software Engineers, AI Engineers, and Applied Scientists and have opportunities to learn about various AI technologies and how they are applied to the semiconductor industry.
You will significantly influence our overall strategy by helping define these product features, drive the system and cloud infrastructure, and spearhead the best practices that enable a quality product.
You are the ideal candidate if you are passionate about new opportunities and have a demonstrated track record of success in delivering new features and products.
A commitment to teamwork and strong communication skills with business and technical partners are important requirements.
Creating reliable, scalable, and high-performance products requires exceptional technical expertise, a sound understanding of the fundamentals of computer science, and practical experience building large-scale systems.
Responsibilities
Design, develop and maintain the infrastructure for Gauss Lab’s products
Design, develop, deploy and maintain a secure, reliable, robust, and scalable micro-services infrastructure for our AI products, which are deployed on the cloud as well as on-prem, with high availability and low latency
Develop and maintain flexible CI/CD solutions that can be used to deploy our product on customer’s kubernetes clusters as well as on public cloud
Architect the monitoring and observability infrastructure for the data and micro-services that make up our AI based products built on multi-modal data (e.
g.
, sensor and image data).
Take responsibility for end-to-end development with high standard on software design, coding, code reviews, tests and automation of deployment within CI/CD disciplines.
Work closely with product/program managers to understand the product’s needs, business problems and domain.
Work cross-functionally with various engineering and data science teams to identify and execute on devops and infrastructure challenges.
Key Qualifications
BS/MS degree in Computer Science and Engineering or strong industry experience in software development.
5+ years of industry experience in building/deploying large scale production systems, software development and/or platform engineering.
3+ years experience in devops, SRE role or related.
Startup spirit with the ability to be flexible and wear multiple hats.
Experience in cluster management, APM tools and integrating monitoring and observability tools such as Prometheus, Grafana, ELK Stack, Kibana, Data Dog, New Relic.
Experience in CI/CD frameworks such as Jenkins, Circle CI, Travis CI, Azure pipelines, Gitlab, Github Actions etc.
Experience in configuring, launching and managing Kubernetes clusters and related tools for these such as like consul, istio.
Experience in configuration management and orchestration tools as well as infrastructure as code tools for example Ansible, Chef, Puppet, Terraform, Cloudformation etc.
Experience in at least one modern programming language such as Python, Java, Go, Rust.
Development experience in a cloud service environment such as Amazon AWS, MS Azure, and Google Cloud Platform as well as on-prem kubernetes clusters in highly secure environments.
Excellent verbal and written communication skills, able to collaborate cross-functionally
Plus: Experience with testing frameworks and automation.
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