Senior Software Engineer - Dev Platform

Jobgether; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Remote work from Brazil

Impactful projects

Modern tech stack

End-to-end ownership

Cross-functional collaboration

Professional growth

Inclusive culture

Job summary

Jobgether is seeking a backend/platform software engineer to build, deploy, and operate APIs and distributed services in production. You will design scalable APIs, SDKs, and developer tools to onboard teams quickly and safely while migrating existing workloads to a secure gateway.

The role emphasizes observability, security, and end-to-end ownership of features across the SDLC. You will collaborate with SRE and security groups, contribute to technical documentation, and help shape the platform

Qualifications

• Experience as a backend or platform software engineer building, deploying, and operating APIs and distributed services in production.
• Strong proficiency in at least one backend language (Rust, Python, or TypeScript) with emphasis on clean, well-tested code.
• Familiarity with LLM APIs, auth, streaming responses, token accounting, rate limits, and provider failures.

Responsibilities

• Build and extend the AI Gateway by integrating models/providers, routing policies, and usage reporting.
• Design and maintain clean APIs, SDKs, and self-service tools for fast onboarding and safe AI usage.
• Support migration of existing LLM workloads to the gateway with minimal disruption.
• Implement access controls, API key management, authentication, and audit logging with security teams.
• Develop observability to monitor latency, errors, token usage, and costs across workloads.
• Own features across SDLC from design to deployment and improvements.
• Collaborate with SRE teams to maintain availability, performance, resilience, and operational quality.
• Provide documentation and troubleshooting support to internal users and incorporate feedback.
• Contribute to code reviews, design discussions, and engineering standards.

Skills

Backend engineering

API design

Cloud knowledge

CI/CD

Problem solving

Cross-functional collaboration

Tools

Kubernetes

Job description

Accountabilities

• Build and extend the AI Gateway by integrating new models and providers, implementing routing policies, and developing budget controls, rate limits, and usage and cost reporting.
• Design and maintain clean, scalable APIs, SDKs, and self-service tools that help engineering teams onboard quickly and use AI services safely.
• Support the migration of existing LLM workloads to the gateway while minimizing disruption to internal users and production systems.
• Implement access controls, API key management, authentication mechanisms, and audit logging in collaboration with security stakeholders.
• Develop observability capabilities that provide teams with visibility into latency, errors, token consumption, and costs across their workloads.
• Own features throughout the software development lifecycle, from technical design and implementation to deployment, monitoring, and ongoing improvements.
• Collaborate with site reliability engineering teams to maintain service availability, performance, resilience, and operational quality.
• Provide clear documentation, troubleshooting support, and technical guidance to internal users, incorporating their feedback into platform improvements.
• Contribute to code reviews, design discussions, technical documentation, and engineering standards across the developer platform team.

Requirements

• Demonstrated experience as a backend or platform software engineer building, deploying, and operating APIs and distributed services in production environments.
• Strong proficiency in at least one backend programming language, such as Rust, Python, or TypeScript, with a commitment to writing clean, maintainable, well-tested code.
• Practical understanding of LLM APIs, including authentication, streaming responses, token accounting, rate limits, and provider failures.
• Experience with observability practices, CI/CD pipelines, and containerized applications, along with working knowledge of Kubernetes and at least one major cloud provider.
• Ability to design well-documented APIs and developer tools for internal customers, balancing technical considerations with usability and user feedback.
• Strong problem-solving skills, clear written and verbal communication, and the ability to take ownership of projects from conception through production.
• A collaborative mindset and the ability to work effectively across engineering, security, and operations teams in a distributed environment.

Nice to have:

• Experience with API gateways, reverse proxies, or traffic management systems.
• Experience building LLM-powered applications or infrastructure, including model routing, caching, evaluation, and cost-control mechanisms.
• Familiarity with authentication and authorization standards and practices, such as OAuth, OpenID Connect (OIDC), and role-based access control (RBAC).
• Contributions to open-source infrastructure, backend systems, or developer-platform projects.

Benefits

• Remote work flexibility: Work remotely from Brazil as part of a globally distributed team.
• Meaningful technical impact: Help shape the infrastructure that enables engineering teams to build and deploy AI-powered solutions.
• Modern engineering environment: Work with LLM providers, distributed services, cloud infrastructure, and developer-platform technologies.
• End-to-end ownership: Drive technical initiatives from design through implementation, deployment, and continuous improvement.
• Cross-functional collaboration: Partner with engineering, security, and reliability specialists to build secure and dependable systems.
• Professional growth: Strengthen your expertise in backend engineering, AI infrastructure, API design, and platform development.
• Inclusive culture: Join an environment that values diverse backgrounds, perspectives, skills, and contributions.