Software Engineer III - Networking Infrastructure Developer
JP Morgan Chase · Buenos Aires, Argentina ·
- Employment
- Full time
- Category
- Software engineering
- Experience
- 5+ years
Job Responsibilities
Lead the development, implementation, and delivery of software-defined networking (SDN) solutions for software-defined datacenters, ensuring timelines, technical requirements, and network performance standards are met across highly-resilient and scalable infrastructure
Design, develop, and implement network automation solutions and infrastructure management platforms using Python, Go, JavaScript, and modern web technologies to reduce manual intervention and improve operational efficiency
Architect and deploy SDN solutions and network orchestration systems across multi-cloud environments (AWS, Azure, GCP, Private cloud), integrating monitoring frameworks with existing tools to ensure infrastructure reliability
Develop and maintain network automation frameworks, APIs, and tooling that integrate with network devices, controllers, and monitoring systems, writing clean, maintainable infrastructure-as-code that adheres to coding standards
Collaborate with network architects, security teams, product owners, and infrastructure engineers in an Agile scrum environment, conducting code reviews and troubleshooting network applications to meet performance and reliability requirements
Mentor junior engineers on network automation and infrastructure-as-code principles while influencing technical direction by evaluating emerging SDN technologies, automation using AI tools, and DevOps methodologies
Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain,
Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required Qualifications, Capabilities, and Skills
Bachelor's Degree in Computer Science, or related field plus 5+ years of experience in network infrastructure development, DevOps networking engineering, or related occupation with formal training or certification on software engineering and network engineering concepts
Strong experience developing software with Python, Go, JavaScript, RUST and Shell Scripting for network automation and infrastructure management, with experience leading development projects in an Agile environment with cross-functional teams
Deep understanding of networking protocols and technologies including BGP, VRF, MPLS, IP, TCP, and UDP as applied to datacenter contexts, with hands-on experience in cloud networking architectures such as VPC, CNI, hybrid cloud connectivity patterns, and engineering experience with VMware NSX-T for software-defined networking solutions including NSX-T logical switching, routing, load balancing, distributed firewall, micro-segmentation, overlay and underlay network configuration
Experience with CI/CD tools (specifically Jenkins) for infrastructure automation pipelines, container orchestration using Kubernetes and containerized network functions, network automation frameworks and infrastructure-as-code practices (Ansible, Terraform)
Exceptional problem-solving and critical thinking skills with ability to decompose complex network infrastructure challenges, perform root cause analysis across distributed systems, debug and optimize both network infrastructure components and automation software, and apply systems thinking to anticipate cascading impacts of changes.
Excellent communication and collaboration skills to work effectively with cross-functional teams including physical network operations, security, and application platform teams, with demonstrated ability to learn quickly, adapt to changing technologies, and make sound technical decisions under pressure.
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
Advanced English skills
Preferred Qualifications, Capabilities, and Skills