AI Engineer
Role details
Job location
Tech stack
Job description
- We move fast, then solidify: We ship early to get real work into lawyers' hands, then invest in stabilizing and improving what matters. Progress beats polish, but quality is non-negotiable.
- High ownership, flexible schedules: We care about outcomes. You're trusted to manage your time and take responsibility for what you ship, closing loops when things break.
- AI-native by default: We use AI everywhere, not just in the product. Our codebase and workflows are designed so humans and agents work together.
- Remote-first, globally aligned: We work as a distributed team, stay tightly aligned through regular syncs, and get together in person when it matters., You will build the systems that make Alaro's product meaningfully useful to lawyers: agents, extraction tools and controllers that automate repetitive work and reliably execute delegated tasks.
At a high level: we are building a Cursor-like experience for legal documents and legal research - where an agent can search, reason over sources, and propose or apply edits while the lawyer stays in control.
This is an engineering-first applied AI role. To succeed, you'll need to understand the full product surface (editor, retrieval, dashboard workflows), so you can spot where an agent should be given control - and ship it end-to-end., * Document editing: an agent proposes changes and generates/applies patches to DOCX documents, built for legal reality: multiple collaborators, tracked changes, strict formatting, and high expectations for correctness.
- Search & retrieval: when a lawyer asks "search legislation" or "find similar contracts in our database," the agent decomposes that into targeted queries, retrieves the right sources, and grounds outputs with citations.
- Deep research workflows: solving legal problems requires iterative investigation, where agents make progress step by step while keeping their active context focused and manageable.
- Training models: fine-tuning models becomes a necessity to optimize the above workflows. As internal data matures, the agent can learn from past interactions to become more intelligent., We're looking for engineers who care deeply about building real systems that work in production, not demos. You're motivated by hard, messy problems, take pride in ownership, and want to see your work used daily by people who depend on it. You enjoy moving fast, learning by shipping, and pushing AI systems into demanding real-world environments.
Requirements
Do you have experience in Python?, * Ship production systems with high ownership and strong engineering judgment
- Are comfortable building production AI and backend systems in Python
- Have built LLM-powered systems beyond basic prompting, with informed views on grounding, tool use, failure modes, evaluation, and iteration loops
- Have hands-on experience training models and running experiments
- Are comfortable operating in ambiguity and translating broad goals into reliable systems
- Are excited to build agents and iterate on them using real-world usage and measurement
Benefits & conditions
- Meaningful ownership: Competitive salary and meaningful equity, with real responsibility and impact from day one.
- Small team, real impact: You'll work closely with founders and a small group of senior engineers, shaping core systems, culture, and how the company operates as it grows.
- AI-first tooling: An unlimited budget for AI coding agents and tools. We expect you to use them heavily, and we design our systems so they can actually help.
- Time together that matters: We bring the whole company together once a year for an offsite in Alaro (Mallorca), and regularly gather the team in one of our offices to align, whiteboard, and plan in person.