Principal AI/ML Architect
tensorops
This is a lead-level role in applied machine learning, which means you'd be architecting production systems from day one—not learning in a junior sandbox. TensorOps works on real problems: conversational copilots, autonomous agents, and decision-support tools for healthcare and finance. As a Principal Architect, you'd own client relationships and technical direction, which builds both depth and business sense early in your career.
Your work involves designing and deploying GenAI systems end-to-end. You'll shape how teams approach Python, FastAPI, LLMs, and infrastructure (AWS, GCP, Kubernetes). You'll make calls on architecture, guide engineers, and translate client needs into technical strategy. This is architecture work, not pure coding—ownership of systems, not individual features.
This role expects serious ML experience and comfort leading technical decisions. If you have shipped production ML systems, understand the full stack from data to deployment, and can articulate trade-offs clearly, you fit. A portfolio of real projects (recommenders, NLP systems, or agentic workflows) matters more than a degree.
Apply through CareerJumpShip with your resume, a brief note on production ML work you've shipped, and a link to relevant code or portfolio pieces.
About this role
Principal ML Architect (Client-Facing, Agentic AI) - Portugal Location: Portugal (Fully Remote) Build the Next Generation of AI Products with TensorOps TensorOps is an applied-machine-learning studio that helps organisations across Europe and North America design, train, and deploy production-grade GenAI systems. Our team blends research depth with pragmatic engineering, and we’re looking for a seasoned architect to lead our client engagements and technical teams in Portugal. What We’re Working On Conversational Copilots: Intelligent assistants that augment and empower knowledge workers. Autonomous Agentic Systems: Sophisticated agents that perform complex research, analysis, and actions for market-leading platforms. High-Performance Search & Recommendation: Building large-scale, low-latency recommender systems, ad-tech platforms, and search solutions. Decision-Support Tools: High-stakes systems for critical applications in healthcare, finance, and e-commerce. Core Stack Python, FastAPI, Docker TensorFlow, LightGBM, CatBoost Open-source & Commercial LLMs LangChain / LangGraph, Langfuse, LlamaIndex MLFlow, Kubeflow AWS and GCP The Role As a Principal ML Architect, you will be the senior technical leader for our most ambitious client projects. You will act as a trusted advisor to clients, a mentor to your engineering team, and the chief architect for complex AI systems. This is a hands-on leadership role that combines deep technical expertise with strategic client management. You will: Lead Technical Strategy & Architecture: Partner with clients to understand their core business challenges and design sophisticated, scalable solutions leveraging machine learning, search, and agentic AI paradigms. Manage Client Engagements: Serve as the primary technical point of contact for client stakeholders, translating complex concepts, managing expectations, and ensuring project success from a technical and business perspective. Lead & Mentor Engineering Teams: Guide a team of talented ML engineers, fostering a culture of excellence, providing technical direction, and taking ultimate responsibility for project delivery. Drive Innovation: Move beyond conventional ML to architect and implement cutting-edge agentic workflows, agent-based modeling, multi-agent systems, and complex RAG pipelines that deliver transformative value. Oversee the Full Project Lifecycle: Steer projects from initial discovery and architectural design through to deployment, monitoring, and iteration, ensuring solutions are robust, efficient, and production-ready. About You 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 is essential. You are comfortable and effective in a consulting or architectural role, capable of leading technical discussions with C-level executives and engineering teams alike. Proven leadership and project management experience. You have successfully led engineering teams and managed the technical delivery of complex software projects. Deep expertise in Python and its data science ecosystem (e.g., Pandas, NumPy, Scikit-learn). Expert-level understanding of modern AI systems. You have deep, practical experience with Large Language Models (LLMs), agentic design patterns (e.g., LangChain/LangGraph), and classical ML at scale. You can speak with authority on topics like Learning to Rank (LTR), recommender algorithms, RAG, and fine-tuning. Strong architectural foundation in software engineering, MLOps, and cloud infrastructure (AWS/GCP). You know how to design for scalability, reliability, and low-latency. A BSc/MS/PhD in Computer Science, Engineering, or a related field, or equivalent practical experience that demonstrates your deep expertise. Why TensorOps? Strategic Impact: Define the technical vision for high-stakes, real-world problems for industry-leading clients. Your work will directly shape client success and our company's reputation. Lead Expert Teams: Guide and collaborate with a team of experienced ML engineers and researchers. Shape our engineering culture and mentor the next generation of talent. Shape Our Future: As a senior leader, you will play a critical role in the direction of our technical offerings and growth. We offer competitive compensation and a clear path for professional and personal development.