Empower the future of AI by building scalable, innovative ML infrastructure and retrieval systems that shape the way organizations leverage AI capabilities.
Location & work model
Wroclaw-based opportunity with an on-site work model.
As a Senior AI Platform Engineer - ML Infrastructure and RAG Systems, you will be working for our client, a leading multinational tech company focused on transforming AI-driven solutions across industries. You will contribute to developing and maintaining internal AI services, APIs, and retrieval systems that serve research, engineering, and operational needs. This role offers a unique chance to influence AI service delivery and support technological innovation at scale.
Your main responsibilities:
- Develop and maintain internal AI services and APIs for production environments.
- Build and optimize RAG pipelines, including document ingestion, embeddings, retrieval, and relevance tuning.
- Manage vector database performance, scalability, and data freshness to ensure high retrieval quality.
- Design clear, well-documented APIs to support internal users and workflows.
- Integrate model serving endpoints into application-layer systems, ensuring low latency and high reliability.
- Define and monitor service objectives related to latency, reliability, and retrieval quality.
- Implement prompt management, versioning, evaluation, and testing frameworks for LLMs.
- Build resilient systems with fallback and degradation mechanisms to ensure continuous operation.
- Implement monitoring, tracing, logging, and quality metrics to oversee AI services' health and performance.
- Manage the lifecycle of AI services including deployment, rollout, updates, and deprecation.
- Participate in operational support and incident response to troubleshoot and resolve issues swiftly.
You're ideal for this role if you have:
- 4+ years of experience in software or platform engineering, with exposure to AI/ML or LLM applications.
- Strong Kubernetes skills and experience working with containerized environments.
- Good knowledge of AWS, networking fundamentals, IAM, and cloud infrastructure.
- Hands-on experience building and operating production RAG systems.
- Familiarity with vector databases and retrieval systems.
- Strong Python programming skills and experience developing production APIs and services.
- Solid understanding of LLM fundamentals, including prompting, token management, and output reliability.
- Excellent communication skills and the ability to work collaboratively across technical and non-technical teams.
It is a strong plus if you have:
- Experience with agentic AI systems and workflow orchestration.
- Knowledge of LLM evaluation frameworks and quality measurement techniques.
- Exposure to model serving platforms and inference optimization.
- Understanding of embedding model trade-offs and retrieval performance tuning.
- Data engineering experience or AI-related data pipelines.
- Relevant AWS or Kubernetes certifications.
Language Required for the role:
Fluent English, with excellent communication skills.
Eligibility for the role:
Only candidates with an existing legal right to work in Europe will be considered for this role.
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Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.