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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Modus Engineering, Ltd. - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Automated Storage and Retrieval Systems, Cloud Engineering, Software Quality, Continuous Integration, Data Cleansing, Information Engineering, Text Processing, Github, Machine Learning, Natural Language Processing, Performance Tuning, Tensorflow, Azure Machine Learning, Search Technologies, Management of Software Versions, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Containerization, AI Platforms, Kubernetes, Low Latency, Atlassian Tools, Machine Learning Operations - **Published:** August 28, 2026 - **Apply:** https://moduscreate.com/careers/7977992003?gh_jid=7977992003 ## About the Role * Strong proficiency in Python and experience developing production-ready AI/ML applications and services. * Solid experience with Machine Learning, including model development, evaluation, optimization, and implementation. * Hands-on experience building applications using Generative AI and Large Language Models (LLMs). * Experience with Deep Learning concepts, neural networks, and modern model architectures. * Practical experience with PyTorch and/or TensorFlow. * Experience with Natural Language Processing (NLP), including areas such as text processing, embeddings, semantic search, classification, or generation. * Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines and working with vector-based retrieval. * Experience integrating AI/ML APIs, foundation models, and third-party AI services into applications. * Understanding of MLOps and model deployment, including versioning, monitoring, CI/CD, and production ML workflows. * Experience with data engineering concepts, including data preparation, transformation, pipelines, and storage for AI/ML workloads. * Strong software engineering fundamentals with a focus on maintainability, scalability, testing, and code quality. * Ability to collaborate effectively with engineers, data teams, product teams, and other stakeholders in a distributed environment. Bonus points: * Experience with LLM fine-tuning, prompt engineering, and model evaluation. * Experience with vector databases, embeddings, and semantic retrieval systems. * Exposure to AI agents, tool/function calling, or multi-agent architectures. * Experience with cloud-based AI/ML platforms, containerization, and orchestration technologies. * Experience implementing AI observability, guardrails, responsible AI, or model governance. * Experience optimizing AI applications for performance, latency, scalability, and cost. ## Description Hiring Remotely in United States of America Entry level Remote Hiring Remotely in United States of America Entry level Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products. The summary above was generated by AI AI Engineer (Python, Machine Learning, Generative AI/LLMs)About Us, We are looking for an AI Engineer to join our engineering team and design, build, and deploy intelligent solutions using modern Machine Learning, Deep Learning, and Generative AI technologies. You'll work across the AI/ML lifecycle, from experimentation and model development to integration and production deployment, collaborating with engineering, product, and data teams to turn complex business challenges into scalable AI-powered solutions., * Building intelligent experiences using modern Machine Learning and Generative AI technologies. * Collaborating closely with engineering, product, and data teams to solve complex problems. * Raising the bar for AI engineering standards, reliability, and responsible development practices. * Exploring emerging AI technologies and continuously improving how intelligent solutions are built and delivered. ## Related Videos - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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