Lead AI Engineer – Generative AI, LLMOps

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🕒 January 15

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Somnio Software

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

🛍️ eCommerce

💳 Fintech

eCommerce • Healthcare • Fintech

Somnio Software is a leading Flutter app development company based in Uruguay, specializing in creating tailored cross-platform applications for various industries. With a focus on full product development, product discovery, and staff augmentation, Somnio aims to help businesses optimize their digital presence and achieve success through innovative solutions. The company is known for its expertise in Flutter, which allows for rapid and cost-effective app development across mobile, web, and desktop platforms, catering to sectors such as healthcare, fintech, education, media, and retail.

📋 Description

• Architect and implement the generative intelligence core of our upcoming project • Design the RAG (Retrieval-Augmented Generation) architectures • Select the appropriate model stacks • Ensure AI outputs are grounded, safe, and performant • Work in lockstep with the Technical Leader to integrate AI services • Mentor the team on AI engineering best practices

🎯 Requirements

• 8+ years of professional experience in Software Engineering • LLM Orchestration Mastery: Deep expertise in frameworks like LangChain, LlamaIndex, or Haystack • RAG Architecture: Proven experience implementing Retrieval-Augmented Generation, including chunking strategies, embedding models, and vector database management (e.g., Pinecone, or pgvector) • Advanced Prompt Engineering: Expertise in systematic prompt optimization, few-shot prompting, and Chain-of-Thought techniques • Model Integration & Selection: Deep understanding of proprietary models (OpenAI, Anthropic, Gemini) and open-source models (Llama 3, Mistral) • Python Proficiency: Expert-level Python skills, including asynchronous programming • Evaluation & Observability: Experience setting up AI evaluation frameworks (e.g., RAGAS, TruLens, or LangSmith) • API & Backend Integration: Ability to design robust APIs (FastAPI/Flask) • English C1: Ability to explain complex AI concepts to stakeholders and non-technical clients. • Fine-tuning Experience: Practical experience fine-tuning open-source models (PEFT, LoRA, QLoRA) • LLMOps & Deployment: Experience with automated deployment of AI models using tools like BentoML, Modal, or AWS SageMaker • AI Security: Knowledge of LLM-specific vulnerabilities and mitigation strategies • Multi-modal AI: Experience working with Vision-Language models or Audio-to-Text/Text-to-Audio pipelines • Product Thinking: A strong sense of "AI UX"; understanding when a feature should be an agentic workflow versus a simple deterministic function.