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Building production-grade AI platform for LLM access and RAG at fintech scale-up. 4+ years leading AI/ML engineering in production required. 30 vacation days, flexible hours, remote option.
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Anforderungen
- 5+ years backend engineering experience
- 4+ years leading AI/ML engineering in production
- 10+ years total experience ideal
- Deep architecture expertise in Java (JVM) and/or Node.js (NestJS)
- Distributed systems expertise
- API expertise
- Microservices expertise
- Messaging/streaming expertise
- Hands-on with LLM orchestration (LangChain/LlamaIndex or custom)
- Hands-on with vector databases (Pinecone, Qdrant, FAISS)
- Hands-on with cloud AI (AWS Bedrock)
- Operation of systems at scale (millions of daily API calls)
- Strong SLOs
- Observability
- Incident management
- MLOps foundations
- Model registries
- Experiment tracking
- CI/CD
- Kubernetes
- IaC (Terraform)
- Security best practices
- Excellent communication skills
- Stakeholder management skills
- Strong product sense
- Focus on shipping user-facing features
- Experience with GPU/accelerator serving and optimization (vLLM, TGI, Triton, ONNX Runtime)
- Cost optimization for LLM workloads (token budgets, dynamic routing, caching)
- Evaluation and safety/red-teaming for generative systems
- Startup/high-growth experience
- Right to work in the EU
Aufgaben
- Own and evolve the AI engineering function
- Transform the ML team from research-heavy to production-grade
- Partner with the CTO on AI strategy
- Build the platform for LLM access, RAG, and backend services
- Ship reliable, scalable AI features
- Hire, mentor, and develop the AI engineering team
- Set the technical bar and operating rhythms
- Establish code and research review practices
- Organize sub-teams with clear ownership and SLOs
- Manage roadmap, capacity planning, and delivery
- Own the LLM gateway with unified APIs and proxy layers
- Implement rate limits, fallbacks, and cost tracking for LLM gateway
- Build high-performance RAG pipelines
- Implement robust observability and safety guardrails for RAG
- Define async contracts, schemas, and eventing patterns with Java/NestJS teams
- Drive low-latency, scalable inference
- Lead end-to-end model and prompt lifecycle
- Establish LLMOps/MLOps practices
- Implement model/prompt registries, CI/CD, and A/B tests
- Conduct offline/online evaluations for models and prompts
- Monitor model drift and cost
- Optimize inference throughput and cost
- Translate company goals into an AI/ML roadmap
- Balance exploration with reliability and cost
- Own build-vs-buy/vendor strategy for AI services
- Manage AI budgets and SLAs
- Implement data privacy, security, and compliance practices
- Track prompt/model lineage and reproducibility
- Define incident response, runbooks, and postmortems for AI features
Berufserfahrung
Ausbildung
Sprachen
Tools & Technologien
Benefits
- 30 vacation days
- Half-day off on Christmas Eve
- Half-day off on New Year's Eve
- Flexible working hours
- Remote work for limited period
- Well-being support
- Sustainable lifestyle support
- Urban Sports/EGYM Club subsidy
- Jobticket subsidy
- JobRad bicycle leasing
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Das Unternehmen ist ein internationales Fintech-Unternehmen, das innovative End-to-End-Lösungen für die Digitalisierung und Verwaltung von Projekt- und Immobilienfinanzierungen anbietet.
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