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GenAI Solution Architect - Presales Engineer (Europe)
GenAI Solution Architect - Presales Engineer (Europe)Gramian Consulting Group • RO
GenAI Solution Architect - Presales Engineer (Europe)

GenAI Solution Architect - Presales Engineer (Europe)

Gramian Consulting Group • RO
În urmă cu 13 zile
Tip loc de muncă
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Descrierea postului

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for Solution Engineers to partner directly with customers and lead the end-to-end delivery of high-impact technical solutions. Successful candidates will need to be able to work with customer teams, translating real-world challenges into production-ready systems that leverage Generative AI, Computer Vision, and Machine Learning. This role is a blend of software engineering, ML engineering, architecture, and consulting. Engineers will design and deploy solutions, integrate models, build custom workflows, and guide customers through successful implementation.

Commitments Required : 8 hours per day

Employment type : Contractor assignment (no medical / paid leave); 100% REMOTE

Duration of contract : 6+ months

Locations : Europe, preference for German speakers

Interview : Technical Assessment, Technical Interview, Cultural Interview

Responsibilities

  • Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements.
  • Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.
  • Lead full project lifecycles : scoping, solution design, development, implementation, testing, deployment, and iteration.
  • Integrate and optimize AI / ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.
  • Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
  • Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.
  • Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.
  • Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.
  • Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.
  • Mentor junior engineers and contribute to internal best practices for FDE delivery.

Requirements

  • 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.
  • German language proficiency preferred
  • Strong proficiency in Python, JavaScript / TypeScript, Go, or similar production-oriented languages.
  • Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.
  • Direct experience with Generative AI (LLMs, multimodal models, vector databased, or RAG) and applying them to real-world problems.
  • Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).
  • Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).
  • Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Excellent communication skills with both technical and non-technical audiences.
  • Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.
  • Willingness and ability to travel frequently.
  • Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.
  • Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).
  • Experience building APIs, microservices, or distributed systems.
  • Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI / CD for ML).
  • Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).
  • Experience in startup or high-growth environments.
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