AI Solutions Engineer

Join Divergent, a technology company revolutionizing the manufacturing industry with its innovative Divergent Adaptive Production System (DAPS). As an AI Solutions Engineer, you will design, develop, and implement cutting-edge AI solutions while serving as the AI Enablement lead for the organization. You will collaborate with cross-functional teams, provide guidance and training on AI best practices, and drive iterative improvements to AI tools and platforms.

• Concevoir, développer et mettre en production des solutions basées sur des modèles de langage et multimodaux.
• Collaborer avec des équipes interfonctionnelles pour intégrer et optimiser les solutions d'IA générative dans les produits et processus.
• Agir en tant que champion interne de l'IA, en fournissant des conseils, des formations et des ateliers sur les meilleures pratiques.

• B.S. in Computer Science/AI/ML (or related) with 3+ years AI/ML engineering experience
• Experience with ML/LLM libraries such as vLLM, LangChain, PyTorch, and HuggingFace
• Understanding of LLMs and multimodal models with their performance considerations and use cases
• Knowledge about prompt engineering, RAG, and building AI Agents
• Ability to create self‑service enablement assets (playbooks, tutorials, reusable component libraries)
• Ability to translate complex technical concepts for non‑technical audiences and collaborate cross‑functionally
• Ability to lawfully access information and technology that is subject to US export controls
• Experience running trainings to teach and promote AI best practices
• Proficient in programming languages such as Python
• Practical experience developing, deploying, and scaling AI Agents in a production environment
• Proven track record of gathering user feedback and iterating on AI tools to improve adoption
• M.S. in Computer Science, AI, ML, or related field
• Proficiency in TypeScript
• Knowledge of ethical AI, compliance frameworks, and safety standards
• Experience with multimodal pipelines and traditional AI/ML methods
• Hands‑on MLOps: CI/CD, Docker, Kubernetes