Associate GitLab Software Engineer, SDLC

About the role

The SDLC team builds mission-critical tooling across the full software lifecycle, used by all Goldman Sachs engineers. As an SDLC Engineer you will sit at the heart of developer experience, making sure code is versioned securely, reviewed expertly, compiles fast, tests thoroughly and is distributed widely. You will deliver CI/CD solutions using modern tooling and stacks such as Java, Go and Python, and support machine learning and AI tooling.

Key responsibilities

• Contribute to the design, implementation and operation of next-generation CI/CD instances, with a focus on security, testing, performance and availability.
• Develop features and improvements to the CI/CD solution, working with vendor-provided software stacks.
• Work with Product Management and other engineering stakeholders to maintain and improve service quality.
• Advocate for improvements to product quality, security and performance.
• Diagnose and solve technical problems in GitLab and the wider SDLC ecosystem.
• Gather metrics, analyse them and report on results.

Required profile

• Technical degree in Computer Science, Engineering, Mathematics or a related field.
• Minimum 3 years of software engineering experience.
• Ability to use Git; professional experience with cloud deployment patterns, notably AWS and HashiCorp Terraform.
• Strong programming skills in at least one of Go, Java, Python, C or C++, preferably in a large-scale financial or technical organisation.
• Knowledge of Linux, networking protocols and topology, and of algorithms, data structures and software design.
• Track record of owning requirements and delivering value.
• Collaborative, self-directed and able to work in a fast-paced, hybrid, asynchronous environment.

Required skills

• Cloud-native architecture in AWS
• Software repositories, build systems and deployment paradigms
• DevOps, SRE and infrastructure expertise
• Linux application operations and Linux internals (preferred)
• Networking (TCP, UDP, DNS, TLS, HTTP, SSH, etc.) and infrastructure-as-code tools such as Docker and Kubernetes (preferred)