J
AI Engineer
Jobrapido
3 hours ago
Full-time
On-site
Milwaukee, Wisconsin, United States
Loopp is an AI Build Studio that partners with founders and enterprises to design, build, and deploy custom AI products and intelligent systems. From autonomous agents and RAG pipelines to multimodal video, image, and voice intelligence tools, Loopp moves fast to take ambitious concepts to production-grade reality.
Role Description
As an AI Engineer at Loopp, you will be responsible for architecting, prototyping, and scaling AI-driven systems and features across our active studio projects. You will work closely with product and cross-functional engineering teams to integrate foundation models, build LLM agents, optimize retrieval pipelines, and deliver production-ready software systems. The ideal candidate thrives in zero-to-one product development, moves quickly with modern AI tools, and understands how to turn complex machine learning techniques into reliable, user-facing features.
Responsibilities
Design, build, and deploy production-grade AI systems, including LLM-powered applications, AI agents, and multimodal integrations (voice, vision, text). Develop scalable backend services and APIs to integrate foundation models (OpenAI, Anthropic, open-source weights) seamlessly into client platforms. Architect and optimize Retrieval-Augmented Generation (RAG) pipelines, vector database setups, and contextual memory solutions. Evaluate, benchmark, and fine-tune AI models for latency, accuracy, cost, and task-specific performance. Build robust testing, monitoring, and fallback mechanisms (Evals/MLOps) to ensure high system reliability and safety in production. Collaborate with product leaders and venture founders to rapidly prototype MVP features and iterate based on real user feedback.
Qualifications
Technical Proficiency: Strong proficiency in Python, TypeScript/JavaScript, and backend development frameworks (FastAPI, Node.js, Next.js). AI & LLM Stack: Hands-on experience building with modern AI orchestration frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), vector databases (Pinecone, Qdrant, Weaviate, pgvector), and API providers. Software Engineering Fundamentals: Solid foundation in REST/GraphQL APIs, asynchronous programming, microservices, and database design (SQL/NoSQL). Cloud & Infrastructure: Familiarity with deploying and scaling cloud applications (AWS, GCP, Vercel, Docker) and configuring CI/CD pipelines. Prototyping & Product Mindset: Ability to rapidly go from idea to working prototype, balancing velocity with code quality and system performance. Collaboration & Communication: Excellent problem-solving skills and the ability to articulate technical tradeoffs clearly in a remote, distributed environment.
Nice to Have
Experience with fine-tuning open-source models (Hugging Face, vLLM, Ollama) and custom model evals. Familiarity with full-stack UI development (React, Next.js, Tailwind CSS) for end-to-end feature delivery. Prior experience in early-stage startups, venture studios, or fast-paced software agencies.
Role Description
As an AI Engineer at Loopp, you will be responsible for architecting, prototyping, and scaling AI-driven systems and features across our active studio projects. You will work closely with product and cross-functional engineering teams to integrate foundation models, build LLM agents, optimize retrieval pipelines, and deliver production-ready software systems. The ideal candidate thrives in zero-to-one product development, moves quickly with modern AI tools, and understands how to turn complex machine learning techniques into reliable, user-facing features.
Responsibilities
Design, build, and deploy production-grade AI systems, including LLM-powered applications, AI agents, and multimodal integrations (voice, vision, text). Develop scalable backend services and APIs to integrate foundation models (OpenAI, Anthropic, open-source weights) seamlessly into client platforms. Architect and optimize Retrieval-Augmented Generation (RAG) pipelines, vector database setups, and contextual memory solutions. Evaluate, benchmark, and fine-tune AI models for latency, accuracy, cost, and task-specific performance. Build robust testing, monitoring, and fallback mechanisms (Evals/MLOps) to ensure high system reliability and safety in production. Collaborate with product leaders and venture founders to rapidly prototype MVP features and iterate based on real user feedback.
Qualifications
Technical Proficiency: Strong proficiency in Python, TypeScript/JavaScript, and backend development frameworks (FastAPI, Node.js, Next.js). AI & LLM Stack: Hands-on experience building with modern AI orchestration frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), vector databases (Pinecone, Qdrant, Weaviate, pgvector), and API providers. Software Engineering Fundamentals: Solid foundation in REST/GraphQL APIs, asynchronous programming, microservices, and database design (SQL/NoSQL). Cloud & Infrastructure: Familiarity with deploying and scaling cloud applications (AWS, GCP, Vercel, Docker) and configuring CI/CD pipelines. Prototyping & Product Mindset: Ability to rapidly go from idea to working prototype, balancing velocity with code quality and system performance. Collaboration & Communication: Excellent problem-solving skills and the ability to articulate technical tradeoffs clearly in a remote, distributed environment.
Nice to Have
Experience with fine-tuning open-source models (Hugging Face, vLLM, Ollama) and custom model evals. Familiarity with full-stack UI development (React, Next.js, Tailwind CSS) for end-to-end feature delivery. Prior experience in early-stage startups, venture studios, or fast-paced software agencies.