Responsibilities

Si le interesa solicitar este empleo, por favor, asegúrese de cumplir los siguientes requisitos que se enumeran a continuación.

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- We are looking for a Senior AI Engineer to design, build, and operate AI systems that solve real business problems across Finom

- You will work on high-impact initiatives across onboarding, customer support, AI accounting, fraud and risk workflows, document understanding, internal automation, and agentic systems used by multiple teams

- This is not a pure research role. It is a hands‑on engineering role focused on delivering production‑grade AI capabilities that create clear value for customers and the business

- Build and ship AI‑powered product and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns

- Own AI systems end‑to‑end: problem framing, architecture, implementation, evaluation, deployment, monitoring, and iteration

- Partner closely with solution managers, domain teams, and engineers to integrate AI into real workflows rather than isolated demos

- Design quality and evaluation frameworks for AI systems, including offline evals, online signals, failure analysis, and continuous improvement loops

- Develop scalable and reliable inference pipelines with strong attention to latency, cost, security, and observability

- Work on use cases such as onboarding, customer care, transaction and document classification, knowledge assistants, fraud detection, and operational automation

- Contribute to AI platform and tooling decisions that improve reuse, speed, and consistency across teams

- Challenge assumptions, propose better approaches, and help shape the roadmap rather than only execute tickets

- Experiment boldly, learn quickly from failures, and turn insights into stronger systems and better practices





- In your first 6 to 12 months, you will:

- Become fully embedded in the team and business domains you support

- Deliver at least one significant AI capability into production

- Generate visible impact through revenue uplift, cost savings, productivity gains, or risk reduction

- Raise the technical bar for how Finom builds, evaluates, and operates AI systems

- Help other teams adopt AI more effectively through strong engineering practice and pragmatic guidance

- Languages: Python, SQL, noSQL

- LLM / AI: OpenAI, Anthropic, LangGraph, Hugging Face, Ollama, PyTorch, OpenClaw

- Patterns: RAG, tool calling, agent workflows, eval pipelines

- Infrastructure: Docker, Kubernetes, AWS / GCP / Azure

- Data / Platform: Vector databases, event‑driven systems, APIs, observability tooling

Qualifications

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- This role is for someone who can move comfortably from prototype to production: shaping the solution, building the system, measuring quality, and improving it over time

- A strong software engineer with deep Python experience and a track record of shipping production systems

- Hands‑on experience with LLM applications, including some of: RAG, tool use, agents, prompt engineering, evals, structured outputs, guardrails, or fine‑tuning

- Autonomous, pragmatic, and able to keep momentum without heavy supervision

- Clear in communication and comfortable working across functions





- Experience with cloud infrastructure and containerized deployments

- Fluent English

- Ability to design meaningful evaluation, monitoring, and continuous improvement loops

- Proven experience building and deploying AI systems in production

- Strong grasp of the fast‑moving AI landscape, with the ability to turn relevant advances into practical product and engineering decisions

- Someone who actively keeps up with the fast‑moving AI landscape and can separate hype from what is actually useful

- Product‑minded xqbhyrx and focused on real user outcomes, not just model outputs

- Curious, proactive, low‑ego, and biased toward action

- Strong at turning ambiguous business problems into robust technical solutions

- Actively experiments with new AI models, tools, and agentic patterns, and can evaluate which approaches are worth productionizing

- Experience integrating AI systems into backend or product workflows

- Strong Python and software engineering fundamentals

- Comfortable across the full lifecycle: prompting, retrieval, experimentation, evaluation, deployment, and production support

- Strong ownership mindset and ability to work through ambiguity

- Experience in fintech, financial services, risk, compliance, or operations‑heavy environments

- Experience with applied ML beyond LLMs, such as classification, anomaly detection, ranking, or document intelligence

- Experience with vector databases, knowledge systems, and retrieval infrastructure

- Experience with model benchmarking, experimentation frameworks, and cost or latency optimization at scale

- Background in startups or as a founder

- Contributions to open‑source or visible side projects in AI

#J-18808-Ljbffr

📌 Senior AI Engineer (Barcelona)
🏢 Finom
📍 Barcelona