AI Platform Engineer

AI Platform Engineer @ Maite.ai

About Us At 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 . We're a team obsessed with our users, radical about truth, infinitely curious, and living in the future.

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.

You'll be joining at a pivotal moment : we're scaling from proof-of-concept to enterprise-grade reliability. Your work will directly impact whether lawyers can trust our AI to handle their most critical cases.

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?

What You'll Do 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 (.docx, PDFs), anonymization, and embedding generation for semantic search

Implement robust monitoring and observability for AI systems in production - track model performance, latency, costs, and reliability. Make our AI transparent and debuggable

Create CI / CD pipelines that automate model deployment, testing, and rollback strategies. Enable the team to ship confidently and frequently

Strengthen security and governance : Implement best practices for data protection, access control, and compliance (critical in legal tech). Protect sensitive client information

Build autonomous AI agent systems : 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

What We're Looking ForRequired : Significant experience building and operating ML / AI systems in production - you've taken models from research to production and kept them running reliably

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)

Nice to Have : Experience with LLM-specific infrastructure (prompt management, fine-tuning pipelines, inference optimization)

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

Contributions to open-source ML tools or frameworks

You Are : User-obsessed : You understand that infrastructure exists to serve end users (lawyers, in our case). You think about reliability from their perspective

A systems thinker : You see the big picture but obsess over details that matter. You know when to build for scale and when to ship fast

Radically honest : You call out problems early, debate ideas openly, and help the team make better decisions through transparency

Infinitely curious : You stay current with ML / AI advances and love experimenting with new tools. You ask "what if?" constantly

Autonomous and proactive : In a small team, you don't wait for instructions. You identify problems and solve them

Pragmatic : You balance "perfect" with "shipped." You know when to take shortcuts and when to invest in quality

A teacher : You document your work, share knowledge, and help others understand complex systems

What We Offer Compensation €43,000 annual salary

Work-Life Balance 100% remote - work from anywhere in Spain

Flexible hours - we care about output, not hours logged. Manage your own schedule

Async-first culture with regular team meetups to stay connected

28 vacation days

Flexible retribution via Coverflex (meals, transport, kindergarten, and more)

Growth & Learning Time to experiment with new AI tools, frameworks, and technologies - we encourage exploration

Work directly with CTO and cross-functional teams on strategic decisions

Shape the ML infrastructure from the ground up - massive ownership and impact

Access to conferences, courses, and learning resources

Impact & Culture Small, high-impact team where your work directly influences product direction

Meaningful mission : Help build a fairer world through legal technology

Culture of radical truth - your ideas matter, regardless of title

Living in the future - we build for where legal tech is going, not where it is

Our Hiring Process We respect your time and aim for a transparent, efficient process :

Application Review (within 5 business days)

We'll review your CV and any materials you share

Initial Call (30 minutes)

Get to know each other, discuss your experience, answer questions

You'll speak with someone from the team

Technical Interview (90 minutes)

Deep dive into MLOps architecture, system design, and problem-solving

Expect discussions about real scenarios we face

You'll meet with engineers and potentially our CTO

Team Fit Interview (45 minutes)

Meet more team members (Q&R, Product)

Discuss collaboration style, values alignment, and culture

Offer or Decision (within 3 business days after final interview)

Total timeline : 2-3 weeks from application to decision

We'll keep you updated at every stage and are happy to answer questions throughout.

Maite.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We encourage applications from candidates of all backgrounds, experiences, and perspectives.

Location Requirement : Must be legally authorized to work in Spain. This is a fully remote position within Spain.

Let's build a fairer world together.