AI Architect

Craftware is a technology company of over 500 experts, empowering large organizations to solve complex business challenges with modern IT solutions - from sales systems and automation to data platforms and AI. We operate where technology must be reliable, secure, and scalable. We deliver end-to-end projects: from analysis and architecture through implementation to development and maintenance. We are a trusted partner of industry leaders such as Salesforce, Veeva, UiPath, and Databricks.

Model: hybrid - two or three times a week

Engagement: full-time

About the project

We are looking for an experienced Platform Architect (AI) to design and scale AI solutions across the organization. You will translate business needs into production-ready architectures spanning computer vision, LLMs, document processing, and data-driven automation.

The first project is a visual similarity search system for automated verification of in-store display compliance against planograms, based on object detection, image embeddings, and vector retrieval.

Responsibilities

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: 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 the technical contact for the AI Security team and involve them in key design decisions.
• Ensure access control, encryption, and protection against adversarial inputs (e.g. spoofed images, prompt injection).
• Verify new third-party integrations against existing security approvals.

Visual Similarity Search Project

• Design the pipeline: product detection visual embedding, OCR, and category classification hybrid vector query planogram matching.
• Select models and components (e.g. RF-DETR, DINOv2) based on accuracy, cost, licensing, and delivery time.
• Define category-specific retrieval strategies (e.g. text-driven for cigarettes, visual-driven for bottles).
• Decide between self-hosted GPU on AWS and managed services (Roboflow Inference, Pinecone).
• Define the API contract with the backend and RELEX integration, including handling of low-confidence matches.
• Set quality thresholds (precision/recall per category, false-positive rate) with the Product Owner.
• Verify license compliance of components (e.g. Apache vs. AGPL-3.0).
• Design the feedback loop for adding field-verified image crops to the index.
• Define data security and retention requirements with AI Security, including GDPR-relevant store photos.

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 (foundation models, vector databases, agentic frameworks, RAG, fine-tuning) and assess their fit.

Requirements

Required Skills & Experience

• 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 a similar tool.
• Experience with vector databases (Pinecone or equivalent), 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 its 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).

What we offer

• B2B contract
• Fully remote service delivery
• Broad range of projects (internal, international) - genuine variety of clients and tasks
• Budget for skills development and certifications as part of the collaboration
• Regular collaboration reviews and discussion of project scope
• Additional benefits available as part of the collaboration
• Networking and team-building events for project teams