AI Engineer – GenAI & Cloud (f/m/x)
⚲ Białystok, Centrum, Bydgoszcz, Gdańsk, Oliwa, Katowice, Kraków, Podgórze, Lublin, Łódź, Śródmieście, Piła, Poznań, Wilda, Rzeszów, Szczecin, Toruń, Warszawa, Mokotów, Wrocław, Fabryczna
Do uzgodnienia
Wymagania
- Python
- LangChain/LangGraph
- Cloud Computing
- GenAI
- AWS
- Google Cloud Platform
- Microsoft Azure
Opis stanowiska
Nasze wymagania:
At least 4 years in software or ML engineering, with hands-on experience shipping AI/ML systems to production
Strong Python skills — not just scripting, but writing maintainable, tested code for production services
Practical experience with AI/ML frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent
Working knowledge of at least one major cloud platform (Azure, AWS, or GCP) and its AI/ML services
Experience with vector databases, embedding models, and retrieval systems in real-world applications
Familiarity with MLOps fundamentals: model versioning, experiment tracking, CI/CD for ML, and monitoring
Ability to work autonomously while collaborating effectively with architects, data engineers, and product teams
Fluent English (both written and spoken)
Fluent Polish required
Residing in Poland required
Mile widziane:
Experience fine-tuning LLMs (LoRA, QLoRA) or working with model training pipelines
Background in classical ML — scikit-learn, XGBoost, time series forecasting, or recommendation systems
Experience with containerized deployments (Docker, Kubernetes) and infrastructure-as-code
Contributions to open-source AI/ML projects or published technical writing
O projekcie:
We need engineers who build AI systems that work outside of a Jupyter notebook. You’ll take architectures designed for real problems and turn them into production services — reliable, observable, and cost-efficient. Your day-to-day will involve writing Python, wiring up cloud infrastructure, and solving the unglamorous problems that make AI actually useful: data quality, latency, evaluation, and deployment.
You’ll work across the generative and classical AI stack — building knowledge-grounded AI systems, integrating LLMs into applications, training and deploying traditional ML models, and keeping it all running in production on Azure, AWS, or GCP.
Zakres obowiązków:
Build and deploy knowledge-grounded AI systems end-to-end: data ingestion, chunking, embedding pipelines, retrieval logic, re-ranking, and response generation
Develop agentic applications — tool integrations, planning loops, memory management, guardrails — using frameworks like LangGraph, LangChain, Semantic Kernel, or equivalent
Implement and maintain ML pipelines for classical use cases: prediction, classification, recommendation, and optimization models
Deploy and optimize model serving infrastructure: API endpoints, batching, caching, GPU utilization, and cost management across cloud environments
Write clean, tested, production-grade Python — not prototype code that someone else has to rewrite
Build evaluation and monitoring pipelines: automated quality checks, drift detection, latency tracking, and human-in-the-loop feedback loops
Work with cloud-native AI services on at least one major platform (Azure, AWS, or GCP) to implement scalable solutions
Collaborate with AI Architects on technical design and with data engineers on data availability and quality
Oferujemy:
Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas
Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market
We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022
Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more
Comfortable workplace – class A offices or remote work
Dozens of fascinating projects for prestigious brands from all over the world – you can change them thanks to Job Changer application
PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers
Investment in your growth – meetups, webinars, training platform and technology blog – you choose
Fantastic atmosphere created by all Sii Power People
At least 4 years in software or ML engineering, with hands-on experience shipping AI/ML systems to production
Strong Python skills — not just scripting, but writing maintainable, tested code for production services
Practical experience with AI/ML frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent
Working knowledge of at least one major cloud platform (Azure, AWS, or GCP) and its AI/ML services
Experience with vector databases, embedding models, and retrieval systems in real-world applications
Familiarity with MLOps fundamentals: model versioning, experiment tracking, CI/CD for ML, and monitoring
Ability to work autonomously while collaborating effectively with architects, data engineers, and product teams
Fluent English (both written and spoken)
Fluent Polish required
Residing in Poland required
Mile widziane:
Experience fine-tuning LLMs (LoRA, QLoRA) or working with model training pipelines
Background in classical ML — scikit-learn, XGBoost, time series forecasting, or recommendation systems
Experience with containerized deployments (Docker, Kubernetes) and infrastructure-as-code
Contributions to open-source AI/ML projects or published technical writing
O projekcie:
We need engineers who build AI systems that work outside of a Jupyter notebook. You’ll take architectures designed for real problems and turn them into production services — reliable, observable, and cost-efficient. Your day-to-day will involve writing Python, wiring up cloud infrastructure, and solving the unglamorous problems that make AI actually useful: data quality, latency, evaluation, and deployment.
You’ll work across the generative and classical AI stack — building knowledge-grounded AI systems, integrating LLMs into applications, training and deploying traditional ML models, and keeping it all running in production on Azure, AWS, or GCP.
Zakres obowiązków:
Build and deploy knowledge-grounded AI systems end-to-end: data ingestion, chunking, embedding pipelines, retrieval logic, re-ranking, and response generation
Develop agentic applications — tool integrations, planning loops, memory management, guardrails — using frameworks like LangGraph, LangChain, Semantic Kernel, or equivalent
Implement and maintain ML pipelines for classical use cases: prediction, classification, recommendation, and optimization models
Deploy and optimize model serving infrastructure: API endpoints, batching, caching, GPU utilization, and cost management across cloud environments
Write clean, tested, production-grade Python — not prototype code that someone else has to rewrite
Build evaluation and monitoring pipelines: automated quality checks, drift detection, latency tracking, and human-in-the-loop feedback loops
Work with cloud-native AI services on at least one major platform (Azure, AWS, or GCP) to implement scalable solutions
Collaborate with AI Architects on technical design and with data engineers on data availability and quality
Oferujemy:
Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas
Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market
We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022
Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more
Comfortable workplace – class A offices or remote work
Dozens of fascinating projects for prestigious brands from all over the world – you can change them thanks to Job Changer application
PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers
Investment in your growth – meetups, webinars, training platform and technology blog – you choose
Fantastic atmosphere created by all Sii Power People
🔍 Dekoder Ogłoszenia
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writing maintainable, tested code for production services
Oczekuje się od Ciebie pisania kodu, który jest nie tylko funkcjonalny, ale także dobrze udokumentowany, przetestowany i łatwy do utrzymania w długim okresie, co wykracza poza proste skrypty.
🟡
Ability to work autonomously while collaborating effectively with architects, data engineers, and product teams
Musisz być w stanie samodzielnie podejmować decyzje i realizować zadania, ale także efektywnie komunikować się i współpracować z innymi zespołami, co może oznaczać potrzebę zarządzania oczekiwaniami i rozwiązywania konfliktów.
🟡
build AI systems that work outside of a Jupyter notebook
Oczekuje się, że będziesz tworzyć systemy AI, które są gotowe do wdrożenia produkcyjnego i działają w środowisku serwerowym, a nie tylko jako prototypy w środowisku deweloperskim.
🟡
reliable, observable, and cost-efficient
Systemy, które będziesz tworzyć, muszą być nie tylko funkcjonalne, ale także stabilne, łatwe do monitorowania i optymalizowane pod kątem kosztów, co wymaga dbałości o szczegóły techniczne i wydajnościowe.
🟡
Your day-to-day will involve writing Python, wiring up clo
Codzienna praca będzie polegać na pisaniu kodu w Pythonie i integrowaniu różnych komponentów, co może oznaczać dużą ilość pracy programistycznej i integracyjnej.