Xentral
Head of AI(m/w/x)
Full-timeRemoteSenior
Augsburg, Berlin, München, Lohne
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NEneoshare AG
Head of AI Engineering(m/w/x)
München, Frankfurt am Main, Berlin
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Productionizing ML models and building unified LLM access for fintech SaaS. 4+ years leading AI/ML production engineering required. 30 vacation days, flexible hours.
Requirements
- 5+ years backend engineering experience
- 4+ years leading AI/ML engineering in production
- 10+ years total experience ideal
- Deep architecture expertise in Java (JVM)
- Deep architecture expertise in Node.js (NestJS)
- Distributed systems expertise
- APIs expertise
- Microservices expertise
- Messaging/streaming expertise
- Hands-on with LLM orchestration (LangChain/LlamaIndex or custom)
- Hands-on with vector DBs (Pinecone, Qdrant, FAISS)
- Hands-on with cloud AI (AWS Bedrock)
- Operation of systems at scale (millions of daily API calls)
- Strong SLOs
- Strong observability
- Strong incident management
- MLOps foundations: model registries
- MLOps foundations: experiment tracking
- MLOps foundations: CI/CD
- MLOps foundations: Kubernetes
- MLOps foundations: IaC (Terraform)
- Security best practices
- Excellent communication skills
- Excellent stakeholder management skills
- Strong product sense focused 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
Tasks
- Transform ML team from research-heavy to production-grade
- Partner with Director of AI on strategy
- Build platform unifying LLM access, RAG, and backend services
- Ship reliable, scalable AI features for banking
- Hire, mentor, and develop high-performing team
- Set technical standards, operating rhythms, and review practices
- Organize sub-teams with clear ownership and SLOs
- Manage roadmap, capacity planning, and delivery
- Own LLM gateway with unified APIs and proxy layers
- Implement rate limits, fallbacks, and cost tracking
- Build high-performance RAG pipelines
- Ensure robust observability and safety guardrails
- Define clean async contracts and eventing patterns
- Drive low-latency, scalable inference
- Lead end-to-end model and prompt lifecycle
- Curate data, train, evaluate, and deploy models
- Establish LLMOps/MLOps practices
- Implement CI/CD, canary/A/B tests, and drift monitoring
- Optimize inference throughput and cost
- Translate company goals into AI/ML roadmap
- Balance exploration with reliability and cost
- Manage build-vs-buy/vendor strategy
- Implement data privacy, security, and compliance
- Track prompt/model lineage and reproducibility
- Define incident response and postmortems
Work Experience
- 10 - 15 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Java
- JVM
- Node.js
- NestJS
- LangChain
- LlamaIndex
- Pinecone
- Qdrant
- FAISS
- AWS Bedrock
- Kubernetes
- Terraform
- vLLM
- TGI
- Triton
- ONNX Runtime
Benefits
Informal Culture
- International & Inclusive Team
- Modern & Dog-friendly Offices
More Vacation Days
- 30 vacation days
- Half-day off on Christmas Eve
- Half-day off on New Year's Eve
Flexible Working
- Flexible working hours
- Hybrid work
Workation & Sabbatical
- Workation
Healthcare & Fitness
- Urban Sports/EGYM Club subsidy
Public Transport Subsidies
- 50% monthly subsidy for Deutschlandticket
Company Bike
- JobRad bicycle leasing
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of neoshare AG and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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NEneoshare AG
Head of AI Engineering(m/w/x)
München, Frankfurt am Main, Berlin
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Productionizing ML models and building unified LLM access for fintech SaaS. 4+ years leading AI/ML production engineering required. 30 vacation days, flexible hours.
Requirements
- 5+ years backend engineering experience
- 4+ years leading AI/ML engineering in production
- 10+ years total experience ideal
- Deep architecture expertise in Java (JVM)
- Deep architecture expertise in Node.js (NestJS)
- Distributed systems expertise
- APIs expertise
- Microservices expertise
- Messaging/streaming expertise
- Hands-on with LLM orchestration (LangChain/LlamaIndex or custom)
- Hands-on with vector DBs (Pinecone, Qdrant, FAISS)
- Hands-on with cloud AI (AWS Bedrock)
- Operation of systems at scale (millions of daily API calls)
- Strong SLOs
- Strong observability
- Strong incident management
- MLOps foundations: model registries
- MLOps foundations: experiment tracking
- MLOps foundations: CI/CD
- MLOps foundations: Kubernetes
- MLOps foundations: IaC (Terraform)
- Security best practices
- Excellent communication skills
- Excellent stakeholder management skills
- Strong product sense focused 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
Tasks
- Transform ML team from research-heavy to production-grade
- Partner with Director of AI on strategy
- Build platform unifying LLM access, RAG, and backend services
- Ship reliable, scalable AI features for banking
- Hire, mentor, and develop high-performing team
- Set technical standards, operating rhythms, and review practices
- Organize sub-teams with clear ownership and SLOs
- Manage roadmap, capacity planning, and delivery
- Own LLM gateway with unified APIs and proxy layers
- Implement rate limits, fallbacks, and cost tracking
- Build high-performance RAG pipelines
- Ensure robust observability and safety guardrails
- Define clean async contracts and eventing patterns
- Drive low-latency, scalable inference
- Lead end-to-end model and prompt lifecycle
- Curate data, train, evaluate, and deploy models
- Establish LLMOps/MLOps practices
- Implement CI/CD, canary/A/B tests, and drift monitoring
- Optimize inference throughput and cost
- Translate company goals into AI/ML roadmap
- Balance exploration with reliability and cost
- Manage build-vs-buy/vendor strategy
- Implement data privacy, security, and compliance
- Track prompt/model lineage and reproducibility
- Define incident response and postmortems
Work Experience
- 10 - 15 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Java
- JVM
- Node.js
- NestJS
- LangChain
- LlamaIndex
- Pinecone
- Qdrant
- FAISS
- AWS Bedrock
- Kubernetes
- Terraform
- vLLM
- TGI
- Triton
- ONNX Runtime
Benefits
Informal Culture
- International & Inclusive Team
- Modern & Dog-friendly Offices
More Vacation Days
- 30 vacation days
- Half-day off on Christmas Eve
- Half-day off on New Year's Eve
Flexible Working
- Flexible working hours
- Hybrid work
Workation & Sabbatical
- Workation
Healthcare & Fitness
- Urban Sports/EGYM Club subsidy
Public Transport Subsidies
- 50% monthly subsidy for Deutschlandticket
Company Bike
- JobRad bicycle leasing
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of neoshare AG and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
neoshare AG
Industry
FinancialServices
Description
Das Unternehmen ist ein internationales Fintech-Unternehmen, das innovative End-to-End-Lösungen für die Digitalisierung und Verwaltung von Projekt- und Immobilienfinanzierungen anbietet.
Not a perfect match?
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