AI Architect – GenAI & Cloud (f/m/x)

AI Architect – GenAI & Cloud (f/m/x)

Sii Sp. z o.o.

Wrocław
Kraków
Rzeszów
Warszawa
Lublin
Bydgoszcz
Białystok
Katowice
Poznań
Łódź
Toruń
Piła
Szczecin
Gdańsk
AI Architecture
Cloud AI Ecosystem
Python
AI/ML Frameworks
MLOps
Generative AI
Knowledge Graphs
Transformer Architectures
Technical Proposal Building

Hexjobs Insights

Role: AI Architect focusing on generative and cloud AI. Responsibilities include client engagements, architecture design, project scoping, and mentoring engineers. Requires 10+ years in software/ml engineering and fluency in English and Polish.

Słowa kluczowe

AI Architecture
Cloud AI Ecosystem
Python
AI/ML Frameworks
MLOps
Generative AI
Knowledge Graphs
Transformer Architectures
Technical Proposal Building

Wymagania

At least 10 years in software/data/ML engineering, with at least 3 years focused on AI/ML architecture at scale, Deep, production-level fluency in at least one major cloud AI ecosystem: Azure, AWS, or GCP, Experience in client-facing roles — comfortable leading technical workshops and presenting to both C-level and engineering audiences, Ability to scope and budget AI projects, including cloud cost modeling, team sizing, and delivery planning, Strong hands-on skills in Python and practical experience with AI/ML frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent, Practical experience building knowledge-grounded AI systems and agent architectures in production — not just prototypes, Solid understanding of transformer architectures and how they affect system design decisions (context windows, latency, cost), Fluent English (both written and spoken), Fluent Polish required, Residing in Poland required, Experience fine-tuning LLMs (LoRA, QLoRA, RLHF/DPO) and understanding when fine-tuning is worth the investment vs. in-context learning, Background in consulting, system integration, or services delivery with exposure to enterprise procurement processes, Contributions to open-source AI/ML projects or published technical writing, Experience with graph databases for knowledge graph-augmented search and reasoning, Background in classical ML — because not every problem needs an LLM

Wyświetlenia: 1
Opublikowanaokoło 15 godzin temu
Wygasaza 30 dni
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