Lead AI Engineer

This is a fully remote position, open to applicants in Spain.

📋 Description

• Design, develop, and manage AI systems that address business challenges within Finom.

• Transition AI solutions from prototype stage to production, encompassing solution design, implementation, quality assessment, and continuous enhancement.

• Lead a team of AI engineers by defining objectives, reviewing designs, collaborating, and providing design direction.

• Take ownership of architecture and document decisions, trade-offs, and discarded alternatives.

• Create and deliver AI-driven solutions for customers and internal use, leveraging LLMs, RAG, tool usage, workflows, and agentic patterns.

• Manage AI systems comprehensively: from problem definition, implementation, and evaluation to deployment, monitoring, and iteration.

• Develop robust, scalable inference pipelines with a focus on latency, cost, security, and observability.

• Set evaluation and quality benchmarks, including offline evaluations, online signals, failure analysis, and improvement cycles.

• Design for accountability, model governance, and compliance with EU AI Act requirements.

• Influence AI platform and tooling choices to enhance reusability, speed, and consistency.

• Collaborate with solution managers, domain teams, and engineers to embed AI into actual workflows.

• Shape product roadmaps, negotiate project scope and sequencing, and halt unsupported initiatives.

• Engage in onboarding, customer support, AI accounting, fraud and risk management, document comprehension, internal automation, and agentic systems.

⛳️ Requirements

• Demonstrated experience in leading a team of engineers, either formally or as a technical lead, with accountability for team outcomes.

• Proven track record in owning the technical direction of a system utilized by multiple teams.

• Experience in swaying product or business strategies through technical rationale.

• Background in directly collaborating with non-technical stakeholders concerning commitments and trade-offs.

• Experience in mentoring engineers through reviews, guidance, and design support.

• Strong ownership mentality and the capability to bring clarity to ambiguous situations.

• Proven experience in building and deploying AI systems in a production environment.

• Proficiency in Python and a strong foundation in software engineering principles.

• Practical experience with LLM applications, including RAG, tool utilization, agents, prompt engineering, evaluations, structured outputs, guardrails, or fine-tuning.

• Experience in integrating AI systems into backend or product workflows.

• Ability to design evaluation, monitoring, and continuous improvement processes.

• Familiarity with cloud infrastructure and containerized deployments.

• Strong understanding of the rapidly evolving AI landscape.

• Fluent in English (C1 level).

• Nice-to-have: experience in fintech, financial services, risk management, compliance, or operations-heavy environments.

• Nice-to-have: applied machine learning experience beyond LLMs, vector databases, benchmarking, experimentation, startup/founder experience, or open-source contributions.

• Familiarity with technologies such as Python, SQL, NoSQL, OpenAI, Anthropic, LangGraph, Hugging Face, Ollama, PyTorch, OpenClaw, Docker, Kubernetes, AWS, GCP, Azure, vector databases, event-driven systems, APIs, and observability tools.

🏝️ Benefits

• Ongoing personal and professional development resources and opportunities.

• Flexibility for travel and the option to work remotely or in a hybrid model across Europe.

• Stock Options Program available to all team members.

• Continuous support and care from the organization.

• Work & Swim Program: one month in a corporate apartment in Cyprus.