Senior Python Developer – Kubernetes & Infrastructure Automation

Senior Python Developer – Kubernetes & Infrastructure Automation

Location: Dallas, TX | Hybrid

Type: Direct Hire

Relocation: Available for non-local candidates

Compensation

Base Salary: $160,000 – $230,000

Bonus: Performance bonus

Benefits: 100% company-paid benefits

Overview

GTN is seeking a Senior Python Developer – Kubernetes & Infrastructure Automation to design, build, and maintain backend services, platform tooling, APIs, and automation frameworks that support scalable infrastructure across a large global environment.

This role is best suited for a core software engineer with strong Python development experience, hands-on Kubernetes exposure, and the ability to work across infrastructure-adjacent systems. The ideal candidate should be software-first, with practical experience building production-quality services, internal tools, automation platforms, and APIs that improve reliability, scalability, and operational efficiency.

This is not a traditional network engineering role. Networking knowledge is helpful, but the primary focus is software engineering, Kubernetes, backend development, and infrastructure automation. The right candidate will be comfortable working with platform engineering, infrastructure, security, and network teams while translating operational needs into scalable software solutions.

The Senior Software Engineer will help build software-driven systems that make infrastructure more programmable, observable, reliable, and self-service across Kubernetes, data center, cloud-adjacent, and network-integrated environments.

Key Responsibilities

Software Engineering & Backend Platform Development

• Design, build, and maintain backend services, APIs, internal tools, and automation platforms that support infrastructure and platform engineering teams.
• Develop clean, maintainable, production-quality code, primarily in Python or similar backend languages.
• Build software systems that improve provisioning, configuration, lifecycle management, observability, reliability, and operational workflows.
• Create internal self-service tooling that enables engineering teams to interact with infrastructure capabilities through software.
• Integrate automation and platform tooling into CI/CD pipelines to support testable, repeatable, and controlled deployments.
• Apply modern software engineering best practices, including automated testing, version control, code review, documentation, maintainable design, and production support.
• Own technical problems from design through implementation, deployment, monitoring, and continuous improvement.

Kubernetes & Infrastructure Automation

• Build and support tooling that operates across Kubernetes, containerized platforms, and distributed infrastructure environments.
• Develop services, controllers, automation, and internal platforms that improve reliability, scalability, and operational efficiency.
• Work with Kubernetes concepts such as deployments, services, ingress, networking, observability, workload orchestration, secrets, policies, and platform operations.
• Support infrastructure-as-code and configuration management workflows using tools such as Terraform, Ansible, Jinja2, or similar technologies.
• Collaborate with platform, security, infrastructure, and network teams to improve deployment patterns, system reliability, and operational standards.
• Evaluate and implement modern engineering practices around service discovery, secrets management, policy-as-code, observability, and platform automation.
• Build tooling that helps standardize infrastructure workflows across complex technical environments.

Infrastructure-Aware Automation & Reliability

• Build software that integrates with infrastructure systems, services, APIs, telemetry, configuration workflows, and operational platforms.
• Apply foundational networking knowledge where needed to support automation related to DNS, TCP/IP, routing concepts, load balancing, segmentation, firewall policy, and connectivity.
• Troubleshoot issues across software, Kubernetes, infrastructure, and network-adjacent layers.
• Implement telemetry, observability, monitoring, and alerting workflows to improve infrastructure visibility and reliability.
• Participate in incident response, root cause analysis, and reliability improvement efforts.
• Partner with infrastructure and network engineering teams to translate operational needs into scalable software, APIs, and automation solutions.
• Help reduce manual operational work through well-designed software, automation, and self-service capabilities.

Required Experience

• Strong software engineering background with experience building backend services, APIs, automation platforms, infrastructure tooling, or internal developer platforms.
• Strong Python development skills or experience with another modern backend language.
• Hands-on Kubernetes experience, including containerized workloads, orchestration concepts, deployments, services, ingress, observability, and platform operations.
• Experience writing clean, maintainable, testable, production-quality code.
• Experience with CI/CD, version control, code review, automated testing, and modern software delivery practices.
• Experience building automation for infrastructure, Kubernetes, platforms, cloud-adjacent environments, or internal engineering tools.
• Familiarity with infrastructure-as-code and configuration management tools such as Terraform, Ansible, Jinja2, or similar technologies.
• Ability to troubleshoot across software, Kubernetes, infrastructure, and platform systems.
• Experience integrating systems through APIs, services, event-driven workflows, or automation pipelines.
• Strong ownership mindset with the ability to take ambiguous technical problems from design through production.
• Working knowledge of networking fundamentals such as TCP/IP, DNS, HTTP, routing concepts, load balancing, firewalls, and network security concepts.

Preferred Experience

• Experience in large-scale data center, cloud, HPC, AI infrastructure, or high-availability environments.
• Experience building platform engineering tools, developer platforms, infrastructure services, automation frameworks, or internal self-service systems.
• Exposure to network automation or network-integrated systems involving Cisco, Arista, Juniper, or similar platforms.
• Familiarity with routing and network technologies such as BGP, OSPF, VRF, VLANs, ACLs, firewall policies, EVPN, or VXLAN.
• Experience with distributed systems concepts such as microservices, fault tolerance, service discovery, data consistency, security, and observability.
• Experience with relational, NoSQL, or graph databases.
• Exposure to event-driven or message-based architectures such as Kafka or RabbitMQ.
• Familiarity with secrets management, policy-as-code, infrastructure security, and platform reliability practices.
• Prior contributions to open-source software, Kubernetes, infrastructure, or automation projects.

Ideal Candidate Profile

The ideal candidate is a hands-on, software-first engineer who enjoys building reliable backend systems, APIs, internal tools, and automation platforms that support complex infrastructure environments. This person should bring strong software development fundamentals, practical Kubernetes experience, and enough infrastructure and networking fluency to collaborate effectively with platform, infrastructure, and network engineering teams.

This role is not intended for someone who is primarily a traditional network engineer with light scripting experience. The strongest fit is a core software engineer with Kubernetes and Python experience who can operate in infrastructure-adjacent environments, understand network-related terminology and dependencies, and build scalable automation that improves reliability, observability, and operational efficiency.