AI Engineer

At Orbitant we are looking for AI Engineers (mid and senior, remote).Antes de solicitar este puesto, por favor, lea la siguiente información sobre esta oportunidad que encontrará a continuación.What is Orbitant?Humanity is living through its greatest acceleration. This is not a trend; it is a civilizational inflection point. The companies that will define the next era are not the ones with the most code, but the ones with the best judgment about what to build, how to architect it, and why it matters.Orbitant exists to provide that thrust. We are looking for engineers who don’t just write code. They make the decisions that determine what to build and why.Our pillars:- Solid engineering, no shortcuts. We build with intent, good practices, and a long-term vision, designing clean, scalable, and maintainable solutions.- Innovation with common sense. We explore emerging technologies, analyze them, and incorporate what truly adds value, avoiding passing trends.- Business-oriented technology.

We always understand the why before the how. Every technical decision aligns with strategic objectives to drive impact and deliver value to the business.At Orbitant we promote:- Teamwork and ownership of your work- Sharing knowledge and learning constantly.- Flexibility and freedom to carry out your work day-to-day.- Push toward a higher orbit, for clients, for the team, and for yourself- Mentoring and being mentored. Constant growth.- Automating and working in an AI-first way, betting on tools that help us.- Enjoying what we do and feeling proud of the result.What are we looking for?At Orbitant we are looking for AI Engineers (mid and senior) specialized in building production-grade systems with LLMs, with experience across different types of projects and environments, but above all with a strong desire to keep growing.Beyond experience, what we value most is attitude and alignment with our values. We are looking for people who:- Enjoy learning in their day-to-day and sharing that knowledge- Feel comfortable communicating with their team and with clients.- Collaborate actively, without fear of asking or proposing.- Bring their own ideas and don’t simply wait to be assigned tasks.- Seek to go a little beyond what is expected, always generating real impact.- Have curiosity, a continuous improvement mindset, and a desire to build things to be proud of.We are looking for people who not only code, but understand the why behind what we do, and want to deliver real value. We don’t hire someone for a project, but people we want to work with long-term.Responsibilities:Among the main responsibilities you will have, we can highlight:- Design, build, and ship to production AI agents and LLM-based systems for national and international clients - from scoping with the client to deployment and operation.- Take projects from pilot to production: define the evaluations that matter, instrument traceability, and ensure that what ships meets the agreed business outcomes.- Implement and maintain RAG systems over client documentation and knowledge: chunking strategy, retrieval, reranking, ingestion pipelines.- Design multi-step agent and workflow architectures (e.g. with LangGraph) - state management, tool use, error recovery, cost management.- Build evals (offline and online) with tools like Langfuse: define metrics, datasets, benchmarks against real outcomes - not against “the demo works”.- Design and integrate MCP servers and connect agents with existing client systems (ERPs, CRMs, internal tools).- Contribute to Orbitant’s internal AI-first platform: reusable skills, libraries, templates, and components that accelerate delivery of future projects.- Question the “why” before the “how” - collaborate with business profiles to define the outcome before the architecture.- Review and improve code (your own and your teammates’), work with legacy code when needed, and maintain high quality standards.- Mentor more junior teammates and share learnings (technical sessions, documentation, code reviews).- Propose new techniques, tools, and processes when they add real value (not for hype).- Be accountable for what you put in production: cost, latency, observability, failures.Requirements:Must-have:- Experience building production systems with LLMs: agents, RAG, generation pipelines, automations.- Solid Python as your main working language.- Hands-on knowledge of an agent/workflow orchestration framework (e.g. LangGraph, LangChain, etc.).- Experience designing and implementing evaluations (evals) and traceability of LLM-based systems (e.g. Langfuse or another observability tool).- Real understanding of prompt engineering: structuring, techniques (few-shot, CoT, structured output, tool use).- Experience with Vector DBs (pgvector, Qdrant, Pinecone, Weaviate, Chroma…) and RAG patterns (chunking, retrieval, reranking).- Ability to reason about trade-offs between providers and models (cost, latency, context window, capabilities) without being locked into a spe