AI Associate Engineer

This position is in person in Miami, FL. About the Role We are expanding our ecosystem of UI applications and looking for a curious, motivated AI Associate Engineer to join our growing AI team. In this entry-level role, you will work alongside our senior AI engineer to research, develop, and integrate AI-powered features, including Generative AI and Large Language Model (LLM) capabilities, across our product suite. This is an ideal opportunity for a recent college graduate who is passionate about artificial intelligence, excited by the rapid evolution of generative AI, and eager to apply academic knowledge in a real-world engineering environment. Key Responsibilities • Assist in designing, developing, and deploying AI and machine learning models, with a focus on generative AI and LLM-based solutions that enhance our UI applications and overall product ecosystem. • Integrate Large Language Models such as GPT, Claude, Llama, and Gemini into applications using APIs, prompt engineering, and orchestration frameworks to deliver intelligent features like chat interfaces, content generation, summarization, and semantic search. • Design, test, and refine prompts and prompt chains while implementing techniques such as retrieval-augmented generation (RAG), fine-tuning, and function calling to maximize LLM output quality and reliability. • Collaborate with cross-functional teams across product, design, and front-end engineering to identify opportunities where generative AI and traditional ML can improve user experience and application performance. • Build and maintain data pipelines for training, validating, and serving ML models in production environments, including vector databases and embedding pipelines for LLM-powered features. • Evaluate and benchmark LLM performance across accuracy, latency, cost, and safety dimensions while implementing guardrails, content moderation, and responsible AI practices for generative outputs. • Conduct research on emerging generative AI tools, foundation models, agent frameworks, and best practices, then share findings with the team and recommend adoption where appropriate. • Support the senior AI engineer in prototyping proof-of-concept solutions such as AI agents, copilots, and intelligent assistants, and help evaluate their viability for production use. • Write clean, well-documented, and testable code while participating in code reviews and contributing to engineering best practices. • Monitor and troubleshoot AI model performance, identify areas for improvement, and iterate on solutions through prompt optimization and model selection. Required Qualifications • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field. Recent graduates are welcome to apply. • Foundational understanding of machine learning concepts such as supervised and unsupervised learning, neural networks, natural language processing, and computer vision. • Understanding of generative AI concepts including Large Language Models, transformer architecture, tokenization, embeddings, attention mechanisms, and the differences between foundation models. • Familiarity with prompt engineering principles, including crafting effective system prompts, few-shot examples, chain-of-thought reasoning, and output formatting techniques. • Programming proficiency in at least one language commonly used in AI and ML, such as Python, JavaScript, or similar. • Familiarity with AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or Hugging Face, along with LLM integration tools like LangChain, LlamaIndex, Semantic Kernel, or equivalent. • Exposure to modern UI development frameworks such as React, Angular, or Vue is a plus. • Strong problem-solving skills and an eagerness to learn new technologies, especially in the fast-moving generative AI landscape. • Effective communication skills with the ability to explain technical AI and LLM concepts to non-technical stakeholders. Preferred Qualifications • Hands-on experience with generative AI or LLM projects through coursework, internships, hackathons, or personal projects, such as building chatbots, RAG applications, AI agents, or fine-tuned models. • Experience working with LLM APIs and platforms like OpenAI API, Anthropic API, Hugging Face Inference, Ollama, or similar services. • Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, or pgvector, and an understanding of retrieval-augmented generation patterns. • Exposure to LLM evaluation and observability tools for monitoring model quality, detecting hallucinations, and optimizing costs. • Familiarity with cloud platforms and AI services like AWS Bedrock, Google Cloud Vertex AI, or Azure OpenAI Service. • Experience with version control using Git, CI/CD pipelines, and agile development methodologies. • Understanding of data structures, algorithms, and software engineering fundamentals. • Interest in responsible AI practices, including fairness, transparency, hallucination mitigation, and ethical considerations for generative AI outputs. What You’ll Learn & Growth Opportunities • Gain hands-on experience building and deploying generative AI and LLM-powered solutions that directly impact real users and products. • Develop deep expertise in prompt engineering, RAG architectures, and LLM integration patterns for production-grade UI applications at scale. • Receive mentorship from a senior AI engineer and collaborate with experienced engineering teams on cutting-edge generative AI projects. • Stay at the forefront of the rapidly evolving LLM and generative AI landscape by attending conferences, pursuing certifications, and engaging with the AI community. • Grow into increasingly senior AI engineering roles as our AI team and product ecosystem expand.