AI Architect

Craftware is a technology company of over 500 experts, delivering end-to-end projects from analysis and architecture through implementation to development and maintenance. They serve large organizations with modern IT solutions in areas including sales systems, automation, data platforms, and AI, and are partners of companies such as Salesforce, Veeva, UiPath, and Databricks.

• 5+ years in software architecture, including 2–3 years in AI/ML systems.
• Strong knowledge of machine learning, deep learning, and LLM architectures.
• Hands-on experience with production computer vision pipelines (object detection, embeddings, vector/hybrid search).
• Familiarity with DETR/YOLO-family models and Roboflow or similar tools.
• Experience with vector databases (e.g., Pinecone), RAG, and agentic frameworks.
• Experience designing multi-signal retrieval or ranking systems.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker) and CI/CD for ML.
• Working knowledge of AWS ML/GPU services (SageMaker, EC2 GPU, Bedrock).
• Ability to evaluate self-hosted vs. managed inference costs.
• Understanding of open-source licensing (AGPL, Apache, MIT) and business impact.
• Pragmatic decision-making under time and budget constraints.
• Experience leading or mentoring engineering teams.
• Excellent communication skills, including with non-technical stakeholders.

Nice to have:

• Experience in retail (product recognition, planograms, display compliance).

Architecture & Technology Selection:

• Design end-to-end AI/ML architectures from PoC to production.
• Select models, frameworks, and tools for each use case.
• Run build vs. buy analyses, including cost modelling and vendor lock-in risk.
• Ensure solutions are scalable, secure, cost-efficient, and compliant with GDPR and the EU AI Act.

MLOps & Production Readiness:

• Define MLOps/LLMOps standards including retraining triggers, drift and quality monitoring, model and data versioning, rollback strategy.
• Work with MLOps engineers on implementation.
• Integrate AI components with existing systems and data infrastructure.

Security & Compliance:

• Act as technical contact for the AI Security team and involve them in key design decisions.
• Ensure access control, encryption, and protection against adversarial inputs.
• Verify new third-party integrations against existing security approvals.

Visual Similarity Search Project:

• Design pipeline: product detection, visual embedding, OCR, category classification, hybrid vector query, planogram matching.
• Select models/components based on accuracy, cost, licensing, and delivery time.
• Define category-specific retrieval strategies.
• Decide between self-hosted GPU on AWS and managed services.
• Define API contract with backend and RELEX integration.
• Set quality thresholds with Product Owner.
• Verify license compliance of components.
• Design feedback loop for field-verified image crops.
• Define data security and retention requirements with AI Security.

Leadership & Communication:

• Provide architectural code reviews and guidance to AI/ML Engineers.
• Mentor engineers on AI architecture patterns and best practices.
• Maintain architecture documentation, diagrams, and decision records.
• Track emerging AI technologies and assess their fit.

Zgodnie z art. 13 ust. 1 i 2 rozporządzenia Parlamentu Europejskiego i Rady (UE) 2016/679 z dnia 27 kwietnia 2016 r. w sprawie ochrony osób fizycznych w związku z przetwarzaniem danych osobowych i w sprawie swobodnego przepływu takich danych oraz uchylenia dyrektywy 95/46/WE (ogólne rozporządzenie o ochronie danych, dalej: RODO) (Dz. Urz. UE L119/1) informujemy o zasadach przetwarzania danych osobowych zgodnie z obowiązującym prawem.