technologies-expected

Expected, Python, LangChain/LangGraph, Cloud Computing, GenAI

technologies-optional

Optional, AWS, Microsoft Azure, Google Cloud Platform

Opis stanowiska

About the project, 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.

Twoje zadania

Your responsibilities, 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

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)

Wymagania

Optional, 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

Co oferujemy

What we offer, AI Grant — Stop talking about AI and start building it. Our AI Grant gives you dedicated budget and resources to turn your wildest AI idea into a working project, backed by two paid weeks to focus on nothing else., AI Center of Excellence — Work alongside specialists in agentic AI, sovereign AI, generative and discriminative AI. This isn’t a siloed team — it’s the people you’ll learn from and build with daily., Your tools, your choice — Full access to AI-powered development tools including Claude, Cursor, and GitHub Copilot. Pick what works best for you., Real project variety — From generative AI for legal document compliance, through agentic systems in manufacturing environments, to enterprise-scale AI platforms, computer vision, and autonomous driving. You won’t get bored., Conference and speaking support — Want to attend conferences? We’ll back you. Want to speak at them? Even better — we’ll support you with dedicated preparation time and bonuses.

recruitment-stages

Recruitment stages, Send your CV, Talk to us about your expectations, Learn more about our projects and choose the best, Start your adventure with Sii!

Opis stanowiska

Sii Sp. z o.o., Sii is the leading technology consulting, digital transformation, engineering, and business services vendor in Poland. We already employ more than 7 300 professionals and implement projects in a variety of industries for clients from many countries around the world. The Great Place to Work title, won 10 times in a row, proves that at Sii, we create a friendly work environment., , Sii ensures that all employment-related decisions are made solely on the basis of qualifications and competencies. We are committed to equal treatment of all individuals, regardless of any protected characteristics, and promoting a diverse and inclusive work environment.

Opis stanowiska

This is how we work,

Opis stanowiska

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.

Twoje zadania

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

Co oferujemy

AI Grant — Stop talking about AI and start building it. Our AI Grant gives you dedicated budget and resources to turn your wildest AI idea into a working project, backed by two paid weeks to focus on nothing else.
AI Center of Excellence — Work alongside specialists in agentic AI, sovereign AI, generative and discriminative AI. This isn’t a siloed team — it’s the people you’ll learn from and build with daily.
Your tools, your choice — Full access to AI-powered development tools including Claude, Cursor, and GitHub Copilot. Pick what works best for you.
Real project variety — From generative AI for legal document compliance, through agentic systems in manufacturing environments, to enterprise-scale AI platforms, computer vision, and autonomous driving. You won’t get bored.
Conference and speaking support — Want to attend conferences? We’ll back you. Want to speak at them? Even better — we’ll support you with dedicated preparation time and bonuses.

Recruitment stages

Send your CV
Talk to us about your expectations
Learn more about our projects and choose the best
Start your adventure with Sii!

AI Engineer – GenAI & Cloud (f/m/x)

Sii