Factorial

AI Product Engineer - Operations Domain

Factorial · Barcelona, Catalonia, Spain

  • On site
  • Full-time
  • $95,000 / year
  • Barcelona, Catalonia, Spain

Job highlights

  • Build AI-native products with LLMs.
  • Design and implement AI skills and workflows.
  • Develop evaluation frameworks for AI quality.
  • Collaborate with Product and Design teams.
  • Own systems from concept to production.

About the role

About the Role

Do you want to help us redefine how AI powers the future of Business Management software, not as an add-on, but as a core part of how people work, decide and grow? We’re looking for engineers who treat AI as central to their craft, are obsessed with building and shipping fast, and care about real impact, not hierarchy or titles.

The Team

The Operations domain sits at the core of Factorial. This is where we build the systems that run the day-to-day reality of work for thousands of companies, systems that must be accurate, compliant and reliable. Our teams own business-critical workflows such as: How employee time is tracked, planned, and managed; How the employee journey is modeled from onboarding to offboarding; How companies represent their organizational structure; How compensation and payroll data are calculated and trusted. Our mission is to turn operational complexity into simple, AI-powered experiences, helping companies run smoothly at scale while keeping humans in control of what matters most.

What You’ll Do

As a Product AI Engineer at Factorial, you’ll help define and build the next generation of our AI-native product using modern AI development practices. You will:

  • Build product using Spec Driven Development: Define clear specifications before shipping — including expected behaviours, constraints, and success criteria — and use them to guide implementation, iteration and evaluation using most powerful LLMs.
  • Design and implement AI Skills: Create reusable, well-scoped AI capabilities that can automate and take actions safely within Factorial’s workflows.
  • Develop and maintain evaluation frameworks (Evals): Measure quality, correctness and reliability of AI outputs using automated and human-in-the-loop evaluations to ensure continuous improvement in production.
  • Apply Retrieval-Augmented Generation (RAG): Build systems that ground AI responses in trusted, up-to-date company data, balancing probabilistic models with deterministic sources of truth.
  • Design human-in-the-loop and agentic workflows: Combine LLMs, rules, and user oversight to automate real business processes while keeping humans in control of critical decisions.
  • Own systems end-to-end: From problem definition and system design to shipping, monitoring and iteration in production.
  • Stay close to our customers: Engineers regularly join customer calls, reviews, and feedback sessions to deeply understand real workflows, pain points, and constraints — ensuring we build the right solutions to real problems, not assumptions.
  • Collaborate closely with Product and Design: Shape how AI is embedded into core user experiences — not as a feature, but as part of the workflow.
  • Share knowledge and raise the bar: Mentor peers, document learnings, and contribute to Factorial’s AI engineering best practices.

Who This Is For

Your title matters less than your mindset. You might be mid, senior, or staff, what we care about is AI as a habit (you’ve built real AI-powered systems or workflows, not just experiments), proven impact (shipped projects, side projects, or contributions that made a measurable difference), product-first thinking (you design complete experiences, not just isolated components), and speed & adaptability (you experiment, learn, and iterate fast). Bonus points if you’ve worked with LLMs, skill-based agents, MCP, or other AI protocols.

Technical Foundation

Strong candidates often have solid software engineering fundamentals (any language — Python is common), experience shipping real products to production, knowledge of APIs, cloud platforms, and system design, and a fast learning curve with new tools and technologies. We care far more about what you’ve built than the stack you used.

How We Work

We are office-first in Barcelona & Madrid, with 20% remote flexibility. We foster a people-first, high-trust culture built on radical candor and ownership. Join our multicultural team (40+ nationalities) building the next generation of business management software.

About Factorial

At Factorial, we’re building the leading business management software for companies of all sizes. Our platform centralizes key workflows across HR, finance, and operations, freeing teams from manual processes so they can focus on what really matters: leading, growing, and taking care of their people. With over 1,200 employees across 7 markets, we serve 700,000+ users and are one of Europe’s fastest-growing SaaS companies, backed by top-tier investors and proudly headquartered in Barcelona. We believe in bold goals, radical ownership, and inclusive collaboration. If you're excited to shape the future of business management technology, we’d love to meet you.

Our Values

We own it: We take responsibility for every project. We make decisions, not excuses. We learn and teach: We're dedicated to learning something new every day and, above all, share it. We partner: Every decision is a team decision. We trust each other. We grow fast: We act fast. We think that the worst mistake is not learning from them. We believe in diverse talent: We welcome applicants from all backgrounds and strongly encourage people of diverse experiences and identities to apply. We believe in inclusion: We are committed to equal opportunities and actively promote workplace inclusion of people with disabilities. If you would like to learn more about our inclusive recruitment processes, you are welcome to indicate so optionally and we will share additional information with you.

Perks of being part of our team

  • High growth, multicultural and friendly environment
  • Alan as private health insurance
  • Healthy life with Wellhub (Gyms, pools, outdoor classes)
  • Save expenses with Cobee
  • Language classes
  • Breakfast in the office and organic fruit
  • Nora discounts
  • Free caffeine and theine
  • Pet Friendly

Key skills/competency

  • AI Product Engineer
  • Artificial Intelligence
  • Product Development
  • Software Engineering
  • LLMs
  • Retrieval-Augmented Generation (RAG)
  • Spec Driven Development
  • Agentic Workflows
  • Customer Focus
  • System Design

Skills & topics

  • AI Product Engineer
  • Artificial Intelligence
  • Product Development
  • LLM
  • RAG
  • Spec Driven Development
  • Agentic Workflows
  • Software Engineering
  • Business Management Software
  • SaaS

How to get hired

  • Tailor your resume: Highlight AI, product development, and LLM experience.
  • Showcase impact: Quantify achievements in past projects and contributions.
  • Demonstrate AI fluency: Emphasize hands-on experience with AI systems.
  • Research Factorial: Understand their mission, values, and AI focus.
  • Prepare for technical deep-dives: Be ready to discuss system design and AI implementation.

Technical preparation

Master LLM basics and prompt engineering.,Build RAG systems for data grounding.,Practice Spec Driven Development.,Design agentic workflows with oversight.

Behavioral questions

Describe building a real AI system.,Share an example of product-first thinking.,How do you ensure speed and adaptability?,Discuss a time you owned a system end-to-end.

Frequently asked questions

What is Factorial's approach to AI in Business Management software?
Factorial aims to integrate AI as a core component of its Business Management software, not just an add-on. They focus on using AI to enhance how people work, make decisions, and grow businesses, particularly within their Operations domain.
What AI technologies and methodologies are important for this AI Product Engineer role?
Key technologies and methodologies include Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Spec Driven Development, and designing human-in-the-loop and agentic workflows. Experience with AI skills and evaluation frameworks is also crucial.
What kind of projects will an AI Product Engineer work on at Factorial?
You'll work on building the next generation of Factorial's AI-native product. This includes designing AI skills, developing evaluation frameworks, applying RAG to ground AI responses, and creating agentic workflows to automate business processes.
How important is prior experience with specific programming languages for the AI Product Engineer role?
Factorial values AI and product-first thinking over specific language expertise. While solid software engineering fundamentals are expected (Python is common), they prioritize what you've built and your ability to learn new tools and technologies quickly.
What is Factorial's work environment like, and what are the remote work options?
Factorial has an office-first approach in Barcelona and Madrid, with 20% remote flexibility. They emphasize a people-first, high-trust culture with radical candor and ownership, and boast a multicultural team with over 40 nationalities.
How does Factorial ensure the quality and reliability of its AI outputs?
Quality and reliability are ensured through developing and maintaining evaluation frameworks (Evals). These frameworks use automated and human-in-the-loop evaluations to measure AI output correctness and drive continuous improvement in production.
What does 'Spec Driven Development' mean in the context of this AI Product Engineer role?
Spec Driven Development at Factorial involves defining clear specifications before shipping code. These specifications include expected behaviors, constraints, and success criteria, which then guide the implementation, iteration, and evaluation processes using LLMs.
What are the career growth opportunities for an AI Product Engineer at Factorial?
The role offers opportunities to shape the future of business management technology, work with cutting-edge AI, and contribute to a rapidly growing SaaS company. The emphasis on learning, sharing knowledge, and impacting real-world workflows supports professional development.
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