Platform Architect (AI)

Quick Facts

• Role: Platform Architect (AI)

Description

Design, implement, and scale AI-driven platform architectures across the organization, translating business needs into production-ready AI/ML solutions. The role covers multiple AI domains (computer vision, language models, document processing, and data-driven automation) with an initial focus on a visual similarity search/embeddings + vector retrieval solution for automated verification of store display compliance. You will own end-to-end architecture from POC to production, drive MLOps/LLMOps practices, create technical documentation, and collaborate with AI Security to ensure secure, scalable, and compliant deployments.

Responsibilities

• Design end-to-end architecture for AI/ML systems (POC → production)

• Select AI technologies, frameworks, and models

• Ensure scalable, secure, cost-efficient, and regulation-compliant deployments

• Integrate AI solutions with existing systems and data infrastructure

• Make build-vs-buy decisions for AI capabilities with cost modeling and vendor lock-in risk analysis

• Lead MLOps/LLMOps practices (retraining triggers, drift/quality monitoring, versioning, rollback) and collaborate with MLOps engineers

• Mentor AI engineers on AI architecture patterns and best practices

• Stay current on the AI landscape (foundation models, vector databases, agentic frameworks, RAG, fine-tuning) and assess applicability

• Create and maintain technical documentation, architecture diagrams, and decision records

• Act as technical liaison to AI Security on design-time controls (data flows, model endpoints, third-party integrations) including encryption and safeguards against adversarial inputs

Project Focus: Visual Similarity Search

• Design and maintain the pipeline: product detection → parallel analysis (visual embedding, OCR, category classification) → hybrid query to the vector database → matching against the planogram

• Choose specific models/components (e.g., RF-DETR vs alternatives, DINOv2 as the embedder) with trade-off evaluation (accuracy, cost, licensing, time-to-delivery)

• Define category-specific query strategies (e.g., different signal weights by category)

• Make hosting and cost decisions (self-hosted GPU on AWS vs managed services such as Roboflow Inference or Pinecone)

• Oversee the API contract between the AI pipeline and the rest of the system (including low-confidence handling)

• Set measurable quality thresholds with the Product Owner (precision/recall and acceptable false-positive rates)

• Verify license compliance of chosen components (e.g., Apache vs AGPL-3.0)

• Plan the improvement loop to feed approved field-verified image crops back into the index

• Coordinate with AI Security on required controls and GDPR-relevant photo retention policies

Requirements

• 5+ years of software architecture experience, with at least 2–3 years focused on AI/ML systems

• Strong understanding of machine learning fundamentals, deep learning, and modern NLP/LLM architectures

• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their AI/ML services

• Experience with MLOps tools (MLflow, Kubeflow, SageMaker) and CI/CD for ML pipelines

• Proficiency in Python; familiarity with PyTorch, TensorFlow, and Hugging Face

• Experience with vector databases, RAG pipelines, and agentic AI frameworks

• Strong data architecture, API, and system integration skills

• Excellent communication skills to explain complex technical concepts to non-technical stakeholders

• Experience leading technical teams or mentoring engineers

• Production computer vision pipeline experience (object detection, embedding models, vector/hybrid search)

• Familiarity with DETR/YOLO-family models and tools such as Roboflow (or comparable alternatives)

• Ability to evaluate cost trade-offs between self-hosted GPU and managed/SaaS inference

• Understanding of open-source model licensing constraints (AGPL, Apache, MIT)

Benefits

• Annual bonus

• Private medical care

• Cafeteria/Multisport

• English lessons subsidized by the company

• Group insurance

• Two additional days off (Good Friday, Friday after Corpus Christi), with possibility to exchange for other holidays

• Employee Referral Bonus Program

• Attractive discounts for products and services at company stations

• Employee stock purchase plan

• Employee Assistance Program (Lyra)

• Training and possibility to develop skills in a wide international environment