Back-End Software Engineer

Location: Hybrid (2 days in office, 3 days WFH)

Salary: $125K – $190K (Based on Experience) + Additional Compensation

Authorization: Must be authorized to work in the US

About the Role:

We are seeking an experienced Back-End Software Engineer to join our cloud infrastructure team, supporting our AI Foundations group. This role focuses on developing server-side logic, managing databases, and ensuring high performance and scalability for a web application in a cloud-based environment. The ideal candidate will possess deep expertise in Kubernetes and cloud platforms such as GCP, AWS, or Azure, and have experience building and maintaining robust, scalable back-end solutions.

As a Back-End Software Engineer, you will be responsible for developing core backend systems, integrating with front-end applications, and ensuring the security, observability, and reliability of our services. You will work closely with cross-functional teams, customers, and product managers to define requirements, design technical solutions, and implement cloud infrastructure using cutting-edge technologies. This role will allow you to leverage your cloud infrastructure skills while contributing to the rapid prototyping of new technologies and solutions that drive industry innovation.

Key Responsibilities:

• Server-Side Development: Build and maintain high-performance backend systems, ensuring seamless database interactions, efficient user authentication, and robust configuration management.
• Kubernetes & Cloud Platform Expertise: Architect, design, and implement solutions on cloud platforms (GCP, AWS, Azure) using Kubernetes-based platforms. Focus on the use of Terraform, Kubernetes operators, and Crossplane for infrastructure provisioning and management.
• Cloud-Agnostic Observability: Design and implement cloud-agnostic observability stacks including Prometheus, Thanos, Loki, Tempo/Jaeger, Open Telemetry, Grafana, and Alert manager to ensure the performance, reliability, and monitoring of cloud applications.
• Platform Security: Implement security practices for platform monitoring and detection using tools such as Falco and ensure compliance with CIS benchmarks.
• Dev Ops & Git Ops: Lead Dev Ops process creation, ensuring best practices around Git Ops and continuous integration/deployment (CI/CD).
• Collaboration & Enablement: Work closely with front-end developers, product managers, and customers to align technical objectives, build cohesive and functional code, and improve user experience. Conduct internal workshops to enable teams with platform knowledge and usage.
• Documentation & Leadership: Provide technical leadership, create and maintain detailed documentation for developed systems, and contribute to the reuse of common components that are well-documented and tested.

Required Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Applied Statistics, or a related field.
• 7+ years of relevant experience in software engineering or related technical fields.
• Expert-level experience with Kubernetes and cloud platform technologies (GCP, AWS, Azure).
• Strong background in cloud infrastructure including provisioning, security, and observability tools (e.g., Prometheus, Loki, Grafana, Falco).
• Experience with Terraform, Kubernetes operators, Crossplane, and Git Ops best practices.
• Strong understanding of Dev Ops processes and CI/CD workflows.
• Excellent problem-solving skills and ability to work autonomously in a fast-paced environment.
• Strong communication skills, especially for presenting complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with AI platforms and foundational technologies in cloud-based environments.
• Prior experience in AI/ML development or infrastructure would be a plus.

Interview Process:

• Phone Screen: 15-minute initial call to assess background and technical fit.
• Technical Interview: 1-hour interview to evaluate deep technical knowledge, particularly in cloud infrastructure, Kubernetes, and related technologies.
• Hiring Manager Interview: 30-minute discussion to align expectations and understand how the candidate fits within the team and culture.
• Onsite Interview: 4-hour in-person interview to test technical skills, problem-solving ability, and collaboration style.