Applied AI Engineer

Material Bank

Applied AI Engineer developing AI-powered experiences for Material Bank. Designing, implementing, and optimizing AI systems that enhance user interaction and product discovery.

Posted 5/12/2026full-timeRemote • 🇺🇸 United StatesSeniorLeadWebsite

Tech Stack

Tools & technologies

CloudJavaScriptPythonTypeScript

About the role

Key responsibilities & impact

Design, build, and deploy end-to-end AI-powered product experiences from concept through production.
Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure.
Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling.
Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning.
Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3.
Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank’s platform.
Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies.
Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities.
Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability.
Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value.

Requirements

What you’ll need

8+ years of experience building and shipping production software, including significant full-stack engineering experience.
Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences.
Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling.
Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems.
Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services.
Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience.
Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight.
Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences.
Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste.
Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred.
Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams.

Benefits

Comp & perks

Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect).
We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
401(k) eligible after your first 90 day's employed!
We sponsor multiple events throughout the year to help out our communities.
We’ll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters!
With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI systemsLLMsembeddingsmultimodal modelsRAG architecturesmulti-agent frameworksJavaScriptTypeScriptPythondata pipelines

Soft Skills

systems thinkingproduct instinctsvisual sensibilityquality assuranceusabilitycraftsmanshipcommunicationcollaborationproblem-solvingcreativity