Square One Resources
1 month ago
AI Architect @ Square One Resources
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Company information
- Company
- Square One Resources
- Location
- Polska Poland
- Posted
- 1 month ago
Job description
- Over 10 years of experience in software architecture, including at least 5 years of practical experience in AI/ML.
- Proven track record of delivering AI-powered features or platforms in real-world enterprise environments or in the developer tooling domain.
- Experience collaborating with product, engineering, and architecture teams to deliver high-business-impact solutions.
- Very good knowledge of the Agile approach and iterative software delivery cycles.
- English proficiency at a minimum of B2 level.
For our client, we are looking for an individual for the position of AI Architect. The person in this role will be responsible for leading the design, development, and integration of AI functionalities across the Client's Developer Platform. This role is to ensure a seamless extension of the automotive middleware configuration tool ecosystem with GenAI solutions, agent systems, and ML-driven workflows.
,[Designing and developing scalable, secure AI systems and integrating them with developer tools., Leading the full lifecycle of AI functionalities: design, experimentation, evaluation, deployment, and optimization., Designing GenAI, RAG, MCP solutions, and agent systems., Building and deploying LLM functionalities using GPT, Claude, Llama, and fine-tuned models., Creating RAG pipelines based on technical documentation, ARXML, EMF models, and knowledge graphs., Designing and implementing ML/DL solutions using PyTorch, TensorFlow, and Hugging Face., Building and maintaining MLOps pipelines: training, validation, inference, monitoring, and model development., Deploying AI solutions in Docker/Kubernetes environments and on AWS, Azure, and GCP clouds., Managing vector and graph databases and designing data pipelines for documentation, code, and configuration data., Implementing security mechanisms, guardrails, monitoring, traceability, and data management., Integrating AI services with APIs, microservices, and enterprise platforms., Ensuring compliance with security, GDPR, governance, and functional safety requirements.] Requirements: AI, Machine learning, PythonRequired skills
- docker
- security
- monitoring
- governance
- python
- aws
- kubernetes
- llm
- pytorch
- agile
- gdpr
- gcp
- azure
- gpt
- claude
- llama
- vector databases
- apis
- machine learning
- genai
- data management
- ai/ml
- microservices
- mcp
- english b2
- mlops pipelines
- tensorflow
- functional safety
- data pipelines
- rag
- traceability
- ai architecture
- hugging face
- ai-powered features
- graph databases
- knowledge graphs
- guardrails
- developer tooling
- enterprise platforms
- agent systems
- ml/dl
- developer platform
- ai architect
- fine-tuned models
- scalable ai systems
- iterative software delivery
- ml-driven workflows
- secure ai systems
- lifecycle of ai functionalities
- arxml
- emf models
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