**Location:**
Eastern Europe
**Timezone:**
CET-aligned
**Level:**
Senior
**Employment Type:**
Full-time
**Overview**
We are seeking a Senior AI Platform Engineer who has architected and deployed production-grade AI systems at scale.
This role is focused on foundational AI platform development, not surface-level integrations. The ideal candidate has built end-to-end AI systems, owned platform architecture decisions, and operated AI infrastructure in real enterprise environments.
You will work on designing and scaling advanced AI systems, including retrieval-augmented generation (RAG), multi-agent orchestration, model optimization, evaluation pipelines, and production infrastructure.
Key Responsibilities
- Architect and build scalable, production-grade AI platforms from the ground up
- Design and deploy advanced RAG systems, including hybrid retrieval, re-ranking, and vector search
- Develop and orchestrate multi-agent AI workflows
- Implement robust evaluation frameworks to monitor relevance, safety, hallucination rates, and alignment
- Lead LLM optimization efforts including fine-tuning, quantization, distillation, and inference performance improvements
- Design and manage cloud-native AI infrastructure using Kubernetes and modern MLOps/LLMOps practices
- Collaborate cross-functionally to ensure AI systems meet enterprise reliability, scalability, and governance standards
- Contribute to technical roadmapping and architectural decision-making
**Required Qualifications**
- 6+ years of experience in software engineering with deep specialization in AI/ML systems
- Proven experience building and scaling production AI platforms (not limited to prototype or integration work)
- Strong Python engineering background with production-quality code
- Experience designing and deploying RAG architectures
- Experience building or orchestrating multi-agent systems
- Hands-on experience with LLM optimization techniques (e.g., PEFT, LoRA, QLoRA, quantization, distillation)
- Experience deploying AI systems using Kubernetes (EKS, GKE, AKS, or similar)
- Experience implementing model evaluation, monitoring, and performance measurement pipelines
- Demonstrated ownership of end-to-end AI system architecture
**Preferred Experience**
- Experience with hybrid search architectures (BM25 + dense retrieval)
- Experience with vector databases such as Weaviate, PgVector, Pinecone, or FAISS
- Experience with LangChain, LangGraph, Microsoft Agent Framework, or similar orchestration frameworks
- Experience building feature stores or model registries
- Experience implementing LLM-as-a-Judge or similar evaluation frameworks
- Experience working in enterprise-scale or high-traffic production environments
- Experience mentoring engineers or leading AI initiatives
What This Role Is Not
**This Position Is Not Focused On**
- Chatbot integrations or surface-level LLM feature implementations
- Prompt engineering without infrastructure ownership
- Frontend-heavy or integration-focused AI roles
We are looking for engineers who have owned foundational AI systems and can demonstrate real-world production impact.
Location Requirements
- Must be based in Eastern Europe
- Must be comfortable collaborating within CET working hours
Eastern Europe
**Timezone:**
CET-aligned
**Level:**
Senior
**Employment Type:**
Full-time
**Overview**
We are seeking a Senior AI Platform Engineer who has architected and deployed production-grade AI systems at scale.
This role is focused on foundational AI platform development, not surface-level integrations. The ideal candidate has built end-to-end AI systems, owned platform architecture decisions, and operated AI infrastructure in real enterprise environments.
You will work on designing and scaling advanced AI systems, including retrieval-augmented generation (RAG), multi-agent orchestration, model optimization, evaluation pipelines, and production infrastructure.
Key Responsibilities
- Architect and build scalable, production-grade AI platforms from the ground up
- Design and deploy advanced RAG systems, including hybrid retrieval, re-ranking, and vector search
- Develop and orchestrate multi-agent AI workflows
- Implement robust evaluation frameworks to monitor relevance, safety, hallucination rates, and alignment
- Lead LLM optimization efforts including fine-tuning, quantization, distillation, and inference performance improvements
- Design and manage cloud-native AI infrastructure using Kubernetes and modern MLOps/LLMOps practices
- Collaborate cross-functionally to ensure AI systems meet enterprise reliability, scalability, and governance standards
- Contribute to technical roadmapping and architectural decision-making
**Required Qualifications**
- 6+ years of experience in software engineering with deep specialization in AI/ML systems
- Proven experience building and scaling production AI platforms (not limited to prototype or integration work)
- Strong Python engineering background with production-quality code
- Experience designing and deploying RAG architectures
- Experience building or orchestrating multi-agent systems
- Hands-on experience with LLM optimization techniques (e.g., PEFT, LoRA, QLoRA, quantization, distillation)
- Experience deploying AI systems using Kubernetes (EKS, GKE, AKS, or similar)
- Experience implementing model evaluation, monitoring, and performance measurement pipelines
- Demonstrated ownership of end-to-end AI system architecture
**Preferred Experience**
- Experience with hybrid search architectures (BM25 + dense retrieval)
- Experience with vector databases such as Weaviate, PgVector, Pinecone, or FAISS
- Experience with LangChain, LangGraph, Microsoft Agent Framework, or similar orchestration frameworks
- Experience building feature stores or model registries
- Experience implementing LLM-as-a-Judge or similar evaluation frameworks
- Experience working in enterprise-scale or high-traffic production environments
- Experience mentoring engineers or leading AI initiatives
What This Role Is Not
**This Position Is Not Focused On**
- Chatbot integrations or surface-level LLM feature implementations
- Prompt engineering without infrastructure ownership
- Frontend-heavy or integration-focused AI roles
We are looking for engineers who have owned foundational AI systems and can demonstrate real-world production impact.
Location Requirements
- Must be based in Eastern Europe
- Must be comfortable collaborating within CET working hours
