North & South America AI Fund – AI Fund / Contract / Remote About The Role We’re seeking a Senior AI Engineer with extensive hands-on experience developing products powered by Large Language Models (LLMs) and Generative AI technologies. This role is ideal for an engineer who brings a depth of experience in machine learning, a strong full-stack background, and a product-driven mindset. You’ll help lead the design and development of advanced AI systems—from building prototypes to scaling production systems. The ideal candidate is excited by the challenge of applying cutting-edge AI in meaningful, user-focused ways, and thrives at the intersection of R&D, engineering, and product. What You’ll Do: • Architect and implement scalable AI systems and applications powered by LLMs and multi-agent frameworks. • Lead end-to-end development efforts, including model integration, infrastructure design, and application logic. • Prototype and deploy GenAI applications that combine retrieval, tool use, reasoning, and interactivity. • Contribute to decision-making around model selection, finetuning, evaluation, and safety mechanisms. • Monitor AI/ML performance in production and drive continuous improvement of prompt, RAG, and agent pipelines. • Stay at the forefront of GenAI developments and bring innovative ideas into the product roadmap. What You Must Bring: • 4+ years of experience working in ML or AI engineering roles, ideally with a focus on NLP or GenAI. • Deep understanding of how modern LLMs work, including transformer architectures, finetuning, and evaluation. • Hands-on experience implementing and optimizing GenAI techniques such as: Tool/function calling, Multi-agent workflows, Retrieval-Augmented Generation (RAG), Finetuning or custom training (e.g., LoRA, PEFT), and Structured prompting and evaluation. • Proficiency with GenAI frameworks and tools (e.g., LangChain, LlamaIndex, Hugging Face, Haystack). • Experience integrating LLMs into real-world applications, including building internal tooling or customer-facing AI features. • Solid foundation in full-stack development or backend systems (Python, TypeScript, FastAPI, etc.). • Experience designing and deploying scalable APIs and cloud infrastructure (AWS, GCP, or Azure). • Proficient with databases (PostgreSQL, MongoDB, or vector DBs like Pinecone or Weaviate). • Comfortable working in agile product teams and balancing experimentation with shipping reliable code. • Strong Git/GitHub collaboration skills and comfort working with CI/CD workflows and containerization (Docker, etc.). Bonus Points: • Experience working in a startup or research-oriented environment. • Prior exposure to open-source AI models (e.g., LLaMA, Mistral, Mixtral) and fine-tuning them. • Publications, technical blog posts, or demos of past AI work.