AI Engineer – GenAI & Cloud (f/m/x)

Sii Poland; Warszawa; On-site; PLN 240,000 - 360,000; Full time

Benefits offered by this job

Great Place to Work

Profit sharing

Medical care

Centre of internal trainings

Many experts you can learn from

Job summary

Sii Poland is looking for engineers to build AI systems that run in production beyond notebooks. You will convert architectures into reliable, observable services on Azure/AWS/GCP, focusing on data quality, latency, and deployment.

You will work across generative and classical AI stacks, integrate LLMs, train models, and keep systems running. The role offers diverse projects and collaboration with AI architects and data engineers.

Qualifications

• At least 4 years in software or ML engineering with production AI/ML experience.
• Strong Python skills written for production services.
• Practical experience with LangChain, LangGraph, Semantic Kernel, or equivalent.
• Experience with Azure, AWS, or GCP and their AI/ML services.
• Experience with vector databases, embeddings, and retrieval systems.
• Familiarity with MLOps: model versioning, experiment tracking, CI/CD for ML, and monitoring.
• Ability to work autonomously while collaborating with architects, data engineers, and product teams.
• Fluent English and Polish; residing in Poland.

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

Skills

Python

AI/ML frameworks

Cloud platforms

Vector databases

MLOps

English

Polish

Autonomy

Tools

Docker

Kubernetes

Job description

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.

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.

Your tasks

• 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

Requirements

• 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

Nice to have

• 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

Job no. JOB-BY4C6

Sii ensures that all hiring decisions are made solely on the basis of qualifications and competence.

We are committed to equal and fair treatment of all, regardless of legally protected characteristics.

At Sii, we promote a diverse and inclusive work environment, in full compliance with applicable anti-discrimination laws.

Benefits For You

• Great Place to Work
• Solid financial situation
• Contracts with the biggest brands
• Centre of internal trainings
• Many experts you can learn from
• Open and accessible management team
• Profit sharing
• Passion Sponsorship program
• Regular integration events and trips
• Comfortable and well-equipped offices
• MySii app
• Medical care