Senior Software Engineer - Dev Platform
- Compensation
- Not disclosed
- Location
- Brazil
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- 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.
Full description
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Software Engineer – Dev Platform based in Brazil.
We are seeking an experienced software engineer to help build and scale an internal developer platform that enables engineering teams to integrate and use AI models efficiently, securely, and reliably. In this role, you will contribute to the development of a company-wide AI Gateway, providing unified access to leading large language model (LLM) providers. You will design APIs, SDKs, and self-service tools that simplify adoption while ensuring strong governance, observability, and cost control. Working across engineering, security, and site reliability teams, you will own features from initial design through production deployment. This is an opportunity to shape the infrastructure behind AI-powered development in a remote, international engineering environment.
Accountabilities
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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.
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Design and maintain clean, scalable APIs, SDKs, and self-service tools that help engineering teams onboard quickly and use AI services safely.
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Support the migration of existing LLM workloads to the gateway while minimizing disruption to internal users and production systems.
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Implement access controls, API key management, authentication mechanisms, and audit logging in collaboration with security stakeholders.
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Develop observability capabilities that provide teams with visibility into latency, errors, token consumption, and costs across their workloads.
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Own features throughout the software development lifecycle, from technical design and implementation to deployment, monitoring, and ongoing improvements.
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Collaborate with site reliability engineering teams to maintain service availability, performance, resilience, and operational quality.
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Provide clear documentation, troubleshooting support, and technical guidance to internal users, incorporating their feedback into platform improvements.
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Contribute to code reviews, design discussions, technical documentation, and engineering standards across the developer platform team.
Requirements
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Demonstrated experience as a backend or platform software engineer building, deploying, and operating APIs and distributed services in production environments.