AI Platform Engineer @ Maite.ai, we're building AI agents that transform how legal professionals work. We don't just want to make lawyers 10% faster - we want to reimagine legal practice entirely. Our mission is simple but ambitious: fight for a fairer world through technology. The Opportunity We're looking for an AI Platform Engineer who will architect and maintain the infrastructure that powers our AI-driven legal platform. This isn't a role where you'll manage existing systems - you'll be building the foundation that takes our AI research from experiments to production-grade tools used by thousands of legal professionals daily.
The Challenge : How do you build infrastructure that's reliable enough for legal work (where accuracy matters), fast enough for real-time document analysis, and flexible enough to integrate the latest AI breakthroughs?
Design and evolve our AI infrastructure across Google Cloud, AWS, and specialized services (Qdrant, Supabase, Sentry) to support multiple LLM providers (OpenAI, Anthropic, Gemini) and vector search at scale
Build and improve AI document processing pipelines including OCR systems, text extraction from complex legal documents (.Implement robust monitoring and observability for AI systems in production - track model performance, latency, costs, and reliability. Create CI/CD pipelines that automate model deployment, testing, and rollback strategies. Implement best practices for data protection, access control, and compliance (critical in legal tech). Design infrastructure for AI agents that can reason, use tools, and complete multi-step legal tasks independently
Collaborate closely with engineers, the Q&R (Quality & Research) team, product, and CTO to understand needs and translate research breakthroughs into production features
Optimize for cost and performance : Ensure we can scale efficiently without burning budget on unnecessary compute
Deep expertise in cloud platforms (Google Cloud and/or AWS) including compute, storage, networking, and managed ML services
Strong Python skills and experience with the ML ecosystem: scikit-learn, PyTorch/TensorFlow, LangChain, LlamaIndex, or similar frameworks
Modern JavaScript/TypeScript expertise with React, Next.js, Node.js, and API design - you'll work in our full-stack codebase and build APIs for AI services
Production Kubernetes experience - deploying, managing, and scaling containerized ML workloads in production environments
Infrastructure-as-code experience (Terraform, CloudFormation, Pulumi) for managing cloud resources
Proven track record building CI/CD pipelines for ML systems - automating training, testing, deployment, and monitoring
Experience with Docker and container orchestration for deploying and scaling ML workloads
Knowledge of vector databases (Qdrant, Pinecone, Weaviate) and semantic search architectures
Monitoring and observability expertise (Sentry, Datadog, Prometheus, Grafana, or equivalent)
Background in document processing systems (OCR, PDF parsing, layout analysis)
Familiarity with security and compliance requirements in regulated industries (legal, healthcare, finance)
Previous experience in early-stage startups or small, high-impact teams
You know when to take shortcuts and when to invest in quality
100% remote - work from anywhere in Spain
~ Flexible hours - we care about output, not hours logged.