Dein persönlicher KI-Karriere-Agent
Platform Engineer(m/w/x)
Designing clear APIs and choosing data models for a secure, model-agnostic AI platform. 3-6 years back-end system development experience required. Equity options.
Anforderungen
- 3-6 years back-end system development (queues, caches, databases, streaming, distributed schedulers)
- Ability to discuss system failure modes and tradeoffs
- Strong TypeScript and Node.js skills
- Opinionated about API design, abstractions, and boundaries
- Infrastructure experience (Terraform, Kubernetes, cloud deployments, networking)
- Experience operating services across AWS, Azure, or GCP
- High drive and self-standards
- Ability to move fast without being pushed
- Desire to do best work of career
- Technical working knowledge of LLM ecosystem (context windows, tool calling, streaming, provider quirks, prompt caching)
- Habit of adding metrics, traces, and structured logs
- Security-first mindset
- Understanding of multi-tenant data isolation as design constraint
- Heavy user of AI tooling in development workflow
- Opinions on effective AI tooling
- Experience compounding output with AI
Aufgaben
- Design clear APIs for shared backend systems
- Choose appropriate data models for system reliability
- Handle failure cases in backend systems
- Write tests for important invariants
- Add useful observability to systems
- Keep abstractions simple for maintainability
- Develop the AI engine for user prompts
- Abstract over multiple AI providers
- Implement prompt caching and routing
- Manage failover across model deployments
- Normalize provider-specific behavior
- Ensure reliable workflow execution
- Support agent steps, conditions, and loops
- Extract structured output from workflows
- Implement human-in-the-loop pauses
- Handle actions across hundreds of integrations
- Optimize context windows for long conversations
- Control costs for model usage
- Develop a code execution service
- Ensure clear isolation for untrusted code
- Control secrets, filesystem access, and network access
- Maintain tenant boundaries
- Build a flexible integration layer
- Support standard REST APIs
- Implement industry standards for tools and agents
- Support Model Context Protocol (MCP)
- Enable agent-to-agent communication
- Shape the future direction of platform areas
Berufserfahrung
- 3 - 6 Jahre
Ausbildung
- Abgeschlossene BerufsausbildungODER
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- TypeScript
- Node.js
- Terraform
- Kubernetes
- AWS
- Azure
- GCP
- AI tooling
Benefits
Attraktive Vergütung
- Equity
Gefällt dir diese Stelle?
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Platform Engineer(m/w/x)
Designing clear APIs and choosing data models for a secure, model-agnostic AI platform. 3-6 years back-end system development experience required. Equity options.
Anforderungen
- 3-6 years back-end system development (queues, caches, databases, streaming, distributed schedulers)
- Ability to discuss system failure modes and tradeoffs
- Strong TypeScript and Node.js skills
- Opinionated about API design, abstractions, and boundaries
- Infrastructure experience (Terraform, Kubernetes, cloud deployments, networking)
- Experience operating services across AWS, Azure, or GCP
- High drive and self-standards
- Ability to move fast without being pushed
- Desire to do best work of career
- Technical working knowledge of LLM ecosystem (context windows, tool calling, streaming, provider quirks, prompt caching)
- Habit of adding metrics, traces, and structured logs
- Security-first mindset
- Understanding of multi-tenant data isolation as design constraint
- Heavy user of AI tooling in development workflow
- Opinions on effective AI tooling
- Experience compounding output with AI
Aufgaben
- Design clear APIs for shared backend systems
- Choose appropriate data models for system reliability
- Handle failure cases in backend systems
- Write tests for important invariants
- Add useful observability to systems
- Keep abstractions simple for maintainability
- Develop the AI engine for user prompts
- Abstract over multiple AI providers
- Implement prompt caching and routing
- Manage failover across model deployments
- Normalize provider-specific behavior
- Ensure reliable workflow execution
- Support agent steps, conditions, and loops
- Extract structured output from workflows
- Implement human-in-the-loop pauses
- Handle actions across hundreds of integrations
- Optimize context windows for long conversations
- Control costs for model usage
- Develop a code execution service
- Ensure clear isolation for untrusted code
- Control secrets, filesystem access, and network access
- Maintain tenant boundaries
- Build a flexible integration layer
- Support standard REST APIs
- Implement industry standards for tools and agents
- Support Model Context Protocol (MCP)
- Enable agent-to-agent communication
- Shape the future direction of platform areas
Berufserfahrung
- 3 - 6 Jahre
Ausbildung
- Abgeschlossene BerufsausbildungODER
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- TypeScript
- Node.js
- Terraform
- Kubernetes
- AWS
- Azure
- GCP
- AI tooling
Benefits
Attraktive Vergütung
- Equity
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Langdock
Branche
IT
Beschreibung
The company focuses on AI and commercial roles, emphasizing the importance of technical minds in understanding products and customers.
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Vollzeitnur vor OrtBerufserfahrenBerlin, Freiburg im Breisgauab 140.000 / Jahr