Principal AI/ML Architect

Role overview

This is a senior, client-facing technical leadership role focused on designing and delivering production-grade AI/ML systems for external organisations. The architect partners with stakeholders to translate business problems into scalable solutions spanning conversational copilots, autonomous agentic systems, search and recommendation platforms, and high-stakes decision-support tools. The position blends hands-on engineering depth with strategic consulting, team mentorship, and end-to-end ownership of complex engagements, and is offered on a fully remote basis in Portugal.

Responsibilities

- Define technical strategy and architecture for ambitious AI/ML engagements, from discovery through deployment, monitoring, and iteration - Act as the primary technical point of contact for client stakeholders, translating advanced concepts and managing expectations across business and engineering audiences - Lead, mentor, and provide technical direction to a team of ML engineers and researchers, taking ultimate accountability for delivery quality - Architect and implement cutting-edge agentic workflows, multi-agent systems, and advanced retrieval-augmented generation pipelines - Design large-scale, low-latency recommender, ad-tech, and search systems engineered for scalability, reliability, and production readiness - Drive innovation beyond conventional ML, shaping how agentic AI paradigms are applied across healthcare, finance, and e-commerce domains

Requirements

- 8+ years of professional experience in machine learning and software engineering, with a proven track record of architecting and delivering large-scale, production-grade AI/ML systems - Significant client-facing experience, comfortable leading technical discussions with C-level executives and engineering teams - Proven leadership and project management background, successfully guiding engineering teams through complex software delivery - Deep Python expertise across the data science ecosystem (Pandas, NumPy, Scikit-learn) plus modern frameworks such as FastAPI and Docker - Expert-level knowledge of LLMs, agentic design patterns (LangChain/LangGraph, LlamaIndex), classical ML at scale, RAG, fine-tuning, and learning-to-rank approaches - Strong architectural foundation in MLOps and cloud infrastructure (AWS and GCP), supported by a BSc/MS/PhD in Computer Science, Engineering, or a related field, or equivalent practical experience

Nice to have

- Hands-on experience with MLOps tooling such as MLflow and Kubeflow for orchestration and experiment tracking - Familiarity with classical model libraries including TensorFlow, LightGBM, and CatBoost, and with both open-source and commercial LLMs - Background applying AI to regulated or high-stakes domains such as healthcare, finance, or e-commerce

Benefits and work setup

- Fully remote working arrangement based in Portugal - Senior leadership seat shaping technical offerings and long-term technical direction - Competitive compensation with a clear path for professional and personal development