Applied AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and launch comprehensive AI-driven product experiences from initial concept to final production.

• Architect and implement scalable AI systems utilizing LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and contemporary data infrastructure.

• Construct production-quality multi-agent workflows and orchestration systems using frameworks like LangGraph, LangChain, Mastra, and bespoke tools.

• Develop and enhance Retrieval-Augmented Generation (RAG) systems, focusing on embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning.

• Create multimodal AI workflows that analyze and interpret images, creative assets, and visual datasets using advanced multimodal LLMs, embedding models, and specialized tools such as SAM2/SAM3.

• Generate AI-assisted experiences for search, discovery, content creation, personalization, and creative workflows across Material Bank’s platform.

• Assess, refine, and elevate AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies.

• Collaborate closely with Product, Design, Engineering, Data, and Executive Leadership to pinpoint high-impact opportunities and convert vague concepts into production-ready AI functionalities.

• Make architectural choices that balance speed, scalability, latency, cost, accuracy, and long-term maintainability.

• Continuously assess emerging AI technologies, models, frameworks, and workflows to discover opportunities that deliver significant business and user value.

⛳️ Requirements

• Over 8 years of experience in building and deploying production software, with considerable full-stack engineering expertise.

• Proven success in designing and implementing production-grade AI/ML systems and AI-driven product experiences.

• Extensive hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or similar custom tools.

• Solid engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems.

• Experience with multimodal models, visual analysis systems, and large-scale image-based AI workflows, including familiarity with contemporary image-generation tools and services.

• Strong systems thinking with the capability to balance trade-offs among latency, cost, scalability, accuracy, reliability, and user experience.

• Proven ability to independently navigate ambiguous challenges from concept to completed product with minimal supervision.

• Strong product instincts, visual sensibility, and a high standard for quality, usability, and craftsmanship in AI-generated experiences.

• Genuine interest in creative fields such as architecture, design, fashion, media, photography, or art, along with an appreciation for aesthetics and taste.

• Preferred open-source contributions, side projects, or publicly demonstrable AI work that showcase curiosity, experimentation, and passion for applied AI.

• Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical teams.

🏝️ Benefits

• Flexible PTO, Sick Days, Paid National Holidays, and additional benefits (ask us about this when we connect).

• We contribute to your medical, dental, vision, and short-term/long-term disability plans and have a robust employee assistance program.

• 401(k) eligibility after your first 90 days of employment!

• We sponsor various events throughout the year to support our communities.

• We’re committed to advancing your career. We encourage creativity and initiative, enabling you to grow and innovate within the company. Most importantly, strive to excel in what truly matters!

• With business units and employees worldwide, Material Technologies has adopted a hybrid working model, allowing department leaders to determine the best approach for their teams, whether that be remote, in-person, or a combination of both.