AI Platform Engineer
⚲ Wrocław
25 000 - 50 000 PLN brutto (UoP)
Wymagania
- Python
- RAG
- AI
- LLM
Opis stanowiska
About the Company
Our client leverages cutting-edge technology and data-driven research to drive their scientific approach to investing. Renowned for their innovative culture and collaborative mindset, they have consistently delivered high-quality returns for their investors.
Role Overview
As an AI Platform Engineer, you will be instrumental in building and operating the internal AI application platform, empowering researchers, developers, and data scientists with LLM-powered tools. You will focus on production AI services, including RAG systems, agentic workflows, and retrieval infrastructure. This role is available due to the company's ongoing growth and commitment to enhancing their AI capabilities.
Key Responsibilities
- Develop and maintain internal AI services and APIs.
- Build and improve RAG pipelines, including document ingestion, embeddings, retrieval, and relevance optimisation.
- Manage vector database performance, scalability, and data freshness.
- Design clear, well-documented APIs for internal users.
- Support agentic workflows and the services they depend on.
- Integrate model serving endpoints into application-layer services.
- Define and monitor service objectives around latency, reliability, and retrieval quality.
- Implement prompt management, versioning, evaluation, and testing frameworks.
- Build resilient systems with fallback and degradation mechanisms.
- Implement monitoring, tracing, logging, and quality metrics across AI services.
- Manage service lifecycle activities, including deployment, rollout, versioning, and deprecation.
- Participate in operational support and incident response.
Key Skills & Experience
- 4+ years of experience in software or platform engineering, with exposure to AI/ML or LLM-based applications.
- Strong Kubernetes experience and familiarity with containerised environments.
- Good knowledge of AWS, networking fundamentals, IAM, and cloud infrastructure.
- Hands-on experience building and operating production RAG systems.
- Experience with vector databases and retrieval systems.
- Strong Python skills and experience building production APIs and services.
- Understanding of LLM fundamentals, including prompting, context management, token constraints, and output reliability.
- Strong communication skills and the ability to collaborate across technical and non-technical teams.
Salary & Benefits
- Salary: highly competitive
- Bonus: Competitive annual performance bonus
- Outstanding benefits
Development & Growth
- Clear path to Senior and Lead roles
- Access to internal training resources and mentoring
- Regular hackathons and conference budgets
This role is perfect for a seasoned AI Platform Engineer looking to make a significant impact within a forward-thinking, technology-driven investment firm. Apply today to be part of a dynamic team that values innovation and excellence.
Our client leverages cutting-edge technology and data-driven research to drive their scientific approach to investing. Renowned for their innovative culture and collaborative mindset, they have consistently delivered high-quality returns for their investors.
Role Overview
As an AI Platform Engineer, you will be instrumental in building and operating the internal AI application platform, empowering researchers, developers, and data scientists with LLM-powered tools. You will focus on production AI services, including RAG systems, agentic workflows, and retrieval infrastructure. This role is available due to the company's ongoing growth and commitment to enhancing their AI capabilities.
Key Responsibilities
- Develop and maintain internal AI services and APIs.
- Build and improve RAG pipelines, including document ingestion, embeddings, retrieval, and relevance optimisation.
- Manage vector database performance, scalability, and data freshness.
- Design clear, well-documented APIs for internal users.
- Support agentic workflows and the services they depend on.
- Integrate model serving endpoints into application-layer services.
- Define and monitor service objectives around latency, reliability, and retrieval quality.
- Implement prompt management, versioning, evaluation, and testing frameworks.
- Build resilient systems with fallback and degradation mechanisms.
- Implement monitoring, tracing, logging, and quality metrics across AI services.
- Manage service lifecycle activities, including deployment, rollout, versioning, and deprecation.
- Participate in operational support and incident response.
Key Skills & Experience
- 4+ years of experience in software or platform engineering, with exposure to AI/ML or LLM-based applications.
- Strong Kubernetes experience and familiarity with containerised environments.
- Good knowledge of AWS, networking fundamentals, IAM, and cloud infrastructure.
- Hands-on experience building and operating production RAG systems.
- Experience with vector databases and retrieval systems.
- Strong Python skills and experience building production APIs and services.
- Understanding of LLM fundamentals, including prompting, context management, token constraints, and output reliability.
- Strong communication skills and the ability to collaborate across technical and non-technical teams.
Salary & Benefits
- Salary: highly competitive
- Bonus: Competitive annual performance bonus
- Outstanding benefits
Development & Growth
- Clear path to Senior and Lead roles
- Access to internal training resources and mentoring
- Regular hackathons and conference budgets
This role is perfect for a seasoned AI Platform Engineer looking to make a significant impact within a forward-thinking, technology-driven investment firm. Apply today to be part of a dynamic team that values innovation and excellence.
🔍 Dekoder Ogłoszenia
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instrumental in building and operating the internal AI application platform
Będziesz odpowiedzialny za całą infrastrukturę platformy AI, od budowy po bieżące utrzymanie i rozwiązywanie problemów.
🔴
empowering researchers, developers, and data scientists with LLM-powered tools
Twoja praca będzie polegała na tworzeniu narzędzi, które inni będą wykorzystywać, co może oznaczać dużą presję na dostępność i stabilność tych narzędzi.
🔴
focus on production AI services
Oczekuje się, że będziesz pracować nad systemami, które są już w użyciu i generują wartość biznesową, co wiąże się z wysokimi wymaganiami co do jakości i niezawodności.
🟡
ongoing growth and commitment to enhancing their AI capabilities
Firma dynamicznie się rozwija w obszarze AI, co może oznaczać szybkie zmiany priorytetów i konieczność adaptacji do nowych technologii i wymagań.
🔴
Define and monitor service objectives around latency, reliability, and retrieval quality
Będziesz musiał samodzielnie określić i mierzyć kluczowe wskaźniki wydajności, co wymaga doświadczenia w definiowaniu metryk i systemów monitorowania.