Software Engineer - AI Tooling Infrastructure

Jobgether; Deutschland; Presencial; EUR 90.000 - 130.000; Jornada completa

Descripción de la vacante

Jobgether is seeking a Software Engineer – AI Tooling Infrastructure based in Germany to build, operate, and scale the backend infrastructure powering AI-driven developer tools. You will own production services, including MCP servers, agent skills, and AI assistants, focusing on reliability, security, performance, and observability in an environment where AI-driven traffic presents unique challenges.

This is a hands-on role with significant ownership over production systems and opportunities to

Formación

• 5+ years building, deploying, and operating production backend services.
• Proficient in TypeScript or Go, with practical working knowledge of the other.
• Designing and maintaining APIs with versioning, error handling, rate limiting, and backward compatibility.
• Strong understanding of OAuth, OpenID Connect (OIDC), JWT, and API authorization in production.
• Good knowledge of PostgreSQL and relational databases.
• Experience with CI/CD pipelines, Docker, containerized deployments, and Infrastructure as Code (IaC).
• Ability to troubleshoot distributed systems using metrics, logs, and traces to identify performance bottlenecks and service failures.

Responsabilidades

• Build, deploy, operate, and scale production backend services supporting AI-powered developer tools.
• Own service architecture and infrastructure decisions, improving system reliability, maintainability, scalability, and deployment processes.
• Define and monitor service reliability objectives (SLOs), track error budgets, and prioritize improvements with SRE teams.
• Participate in on-call rotation, investigate production incidents, coordinate resolutions, and develop incident reports and runbooks.
• Manage operational support requests and identify recurring issues for long-term improvements.
• Design and maintain authentication and authorization systems for AI agents and machine clients, including OAuth applications, tokens, and permissions.
• Establish and maintain comprehensive observability through metrics, tracing, logging, dashboards, and alerting systems.
• Manage AI agent traffic, implementing rate limits, capacity controls, and safeguards against traffic spikes.
• Collaborate with Platform, SRE, Authentication, Billing, and Edge Functions teams to improve shared infrastructure and release processes.

Conocimientos

TypeScript

Go

APIs design

OAuth/OIDC/JWT

PostgreSQL

CI/CD

Docker

Infrastructure as Code

Herramientas

Docker

OpenTelemetry

Grafana

Logflare

Descripción del empleo

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer – AI Tooling Infrastructure based in Germany. We are looking for an experienced Software Engineer to build, operate, and scale the backend infrastructure powering innovative AI‑driven developer tools.

In this role, you will take ownership of production services, including infrastructure supporting AI agents, developer assistants, and Model Context Protocol (MCP) integrations. You will focus on ensuring reliability, security, performance, and observability in an environment where AI‑driven traffic introduces unique infrastructure challenges.

Working closely with platform, security, and infrastructure teams, you will help shape scalable architectures and improve operational excellence.

This is a hands‑on engineering position offering significant ownership over systems running in production. You will join a globally distributed, asynchronous engineering environment that values autonomy, open‑source development, and continuous improvement.

Responsibilities

• Build, deploy, operate, and scale production backend services supporting AI-powered developer tools, including MCP servers, agent skills, and AI assistants.
• Own service architecture and infrastructure decisions, improving system reliability, maintainability, scalability, and deployment processes.
• Define and monitor service reliability objectives (SLOs), track error budgets, and prioritize improvements in collaboration with Site Reliability Engineering (SRE) teams.
• Participate in the team's on-call rotation, investigate production incidents, coordinate resolutions, and develop incident reports, runbooks, and preventive solutions.
• Manage operational support requests and identify recurring issues that can be addressed through long‑term engineering improvements.
• Design and maintain authentication and authorization systems for AI agents and machine clients, including OAuth applications, scoped tokens, permissions, and secure access management.
• Establish and maintain comprehensive observability through metrics, distributed tracing, logging, dashboards, and alerting systems.
• Manage AI agent traffic, implementing rate limits, capacity controls, cost safeguards, and mechanisms to handle dependency failures and unexpected traffic spikes.
• Collaborate with Platform, SRE, Authentication, Billing, and Edge Functions teams to improve shared infrastructure, release processes, security, and operational practices.
• Contribute to the development of AI tooling infrastructure, ensuring that reliability, security, and performance remain central to engineering decisions.

Requirements

• At least 5 years of experience building, deploying, and operating production backend services, including participation in on‑call rotations.
• Strong programming skills in TypeScript or Go, with practical working knowledge of the other language.
• Proven experience designing and maintaining APIs, including versioning, error handling, rate limiting, and backward compatibility.
• Strong understanding of OAuth, OpenID Connect (OIDC), JWT, and API authorization, with the ability to troubleshoot authentication and permission issues in production environments.
• Good knowledge of PostgreSQL and relational database systems.
• Experience with CI/CD pipelines, Docker, containerized deployments, and Infrastructure as Code (IaC).
• Ability to troubleshoot distributed systems using metrics, logs, and traces to identify performance bottlenecks and service failures.
• Strong written and verbal communication skills, with the ability to collaborate across teams and work effectively in globally distributed, asynchronous environments.
• Adaptability, ownership, and the ability to navigate ambiguity while delivering solutions in fast‑paced engineering environments.

Preferred

• Experience with AI agent tooling, Model Context Protocol (MCP), or infrastructure serving AI agents and LLM clients.
• Experience extracting services from larger codebases while maintaining compatibility with existing integrations.
• Familiarity with observability platforms such as Grafana, OpenTelemetry, or Logflare, along with practical experience implementing SLOs.
• Contributions to open‑source projects, particularly within the Node.js, Go, TypeScript, or API tooling ecosystems.