Job Overview: Our client is looking for a Platform Software Engineer (Golang, Kubernetes, Internal Developer Platform) to contribute in the development of scalable, modern platforms that power critical business services and support our continued evolution in cloud-based technologies. Experience with AI application development using modern LLM platforms, including agentic workflows, skills/tool definitions, prompt engineering, model evaluation, or integration with commercial and open-source AI models.
Numbers & Facts
Location
Atlanta, GA
Salary
$100,000–$130,000 Per Year
Description
Job Overview:
Our client is looking for a Platform Software Engineer (Golang, Kubernetes, Internal Developer Platform) to contribute in the development of scalable, modern platforms that power critical business services and support our continued evolution in cloud-based technologies.
As a part of a technical team within the end-to-end software lifecycle from development and build systems to testing, release automation, and platform operations. The scope of work is broad and includes software development, CLI tooling, CI/CD pipelines, infrastructure as code development, and root cause analysis of complex engineering issues.
This role is ideal for engineers who enjoy solving complex technical challenges, working across different layers of the stack, and building systems that are robust, scalable, and impactful.
Must-haves
Kubernetes CRDs and custom operators.
Golang CLI tool development.
GraphQL backend with Golang.
Internal developer platform engineering.
Responsibilities:
Design, build, test, operate, and continuously improve platform engineering solutions.
Own technical problems end-to-end, collaborating with stakeholders and engineering teams to deliver scalable, reliable solutions.
Contribute to product and platform roadmaps with consideration for performance, reliability, observability, operability, and testability.
Participate in root cause analysis, incident investigation, troubleshooting, and continuous improvement efforts.
Diagnose and resolve issues across internal systems and downstream dependencies, partnering with other teams when necessary.
Follow established engineering standards, contribute to technical discussions, and provide constructive feedback to improve processes and tooling.
Demonstrate strong teamwork, accountability, and a growth mindset through continuous learning and collaboration.
Basic Qualifications:
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
3+ years of professional software engineering experience.
Experience developing software in Linux or macOS environments.
Proficiency in at least one modern programming language, preferably Golang.
Strong understanding of software engineering fundamentals, including data structures, algorithms, and system design.
Familiarity with distributed systems concepts and modern software architectures.
Experience using Git-based source control workflows (GitHub, GitLab, or similar).
Exposure to containerized application development using Docker and Kubernetes.
Familiarity with cloud platforms, preferably Google Cloud Platform (GCP).
Strong desire to learn and contribute across a broad technical landscape.
Preferred Qualifications:
Professional experience developing applications or tooling in Golang.
Experience building and updating GraphQL types, queries, and mutations for backend Golang APIs.
Experience designing, operating, or supporting distributed systems with consideration for scalability, performance, availability, and observability.
Experience with platform engineering practices and tools, including GitOps, CI/CD, OCI artifacts, test infrastructure, or build systems.
Experience working with Kubernetes clusters and associated ecosystem components.
Familiarity with infrastructure-as-code and developer productivity tooling.
Experience contributing to open-source projects.
Stand-out Qualifications:
Professional experience administering or developing with Bazel or other large-scale build systems.
Experience with AI application development using modern LLM platforms, including agentic workflows, skills/tool definitions, prompt engineering, model evaluation, or integration with commercial and open-source AI models.
Experience developing CLI tools and developer workflows.
Experience creating or maintaining Kubernetes Custom Resource Definitions (CRDs) and custom controllers/operators.
Experience troubleshooting complex build, deployment, or infrastructure-related issues across large distributed systems.
Experience with developer platforms or internal engineering productivity initiatives.
General knowledge, skills and abilities:
Working knowledge of Google Cloud Platform and cloud-native technologies.
Understanding of modern software development methodologies, including Agile and iterative development practices.
Strong analytical and problem-solving skills with an ability to investigate complex technical issues.
Effective verbal and written communication skills, with the ability to communicate technical concepts to both technical and non-technical audiences.
Ability to estimate work, manage priorities, and deliver commitments within a team environment.
Understanding of infrastructure and systems concepts, including networking, compute, storage, security, containers, and platform operations.
Positive attitude, strong work ethic, and commitment to continuous improvement and collaboration.