AI Gen & ML Engineer
Flanks
AI Gen & ML Engineer
A little bit about Flanks 🚀
Flanks is shaking up the wealth management industry by making it simpler and way more efficient for financial institutions. Our SaaS platform is designed to help banks, family offices, and wealth managers get a full picture of their clients' financial assets—all in one place. 💼💡
Founded in 2019 and based in Barcelona, we’ve brought together a team of passionate wealth management and tech pros, all with a shared goal: to change how wealth management is done. Backed by €9.8 million in investment, we’re growing fast, and we’re not stopping anytime soon! 📈🔥
What we stand for:
- People First 🤝 – our team comes first. We want every Flanker to feel at home, engaged, and part of something bigger.
- Keep Growing 🌱 – as the company grows, so should you. We’re all about personal and professional development here.
- Think Twice, Act Once 🧠💭 – we believe in thoughtful decisions, considering the impact on both our team and our clients before taking action.
If you’re looking for a place where you can grow and make an impact at a fast-paced, exciting fintech startup, this might just be the place for you! 🎯✨
About the role 💼
We’re looking for an AI Gen & ML Engineer to join our growing team. You’ll play a key role in designing, building, and deploying cutting-edge AI solutions that power the next generation of wealth management tools.
What you'll do 🛠️
Here’s what you can expect to work on:
- Design, train, and deploy classical ML models (e.g., Random Forest, XGBoost, Logistic Regression) and deep learning architectures (e.g., CNNs, RNNs, Transformers) for financial applications.
- Fine-tune and evaluate large language models (LLMs) for domain-specific use cases, contributing to solutions such as tax optimization, conversational analytics, and portfolio recommendations.
- Develop and orchestrate multi-agent systems, leveraging frameworks like LangGraph, CrewAI, LlamaIndex, or OpenLangChain to build collaborative, context-aware AI workflows.
- Build and maintain robust, production-grade ML pipelines with proper observability, versioning, testing, and deployment practices in real environments.
- Collaborate cross-functionally with product, data, and engineering teams, while staying up to date with the latest trends in GenAI, MLOps, and emerging research in the AI/ML ecosystem.
What we'd love to see 😍
- Strong proficiency in Python, Git workflows, and containerization with Docker.
- Comfort working in collaborative development environments (GitHub, pull requests, CI/CD pipelines).
- Ability to write clean, testable, and maintainable code, including unit and integration testing practices.
- Strong understanding of API development using FastAPI (or similar) and RESTful design principles.
- Solid experience with ML and DL frameworks such as scikit-learn, PyTorch, or TensorFlow.
- Working knowledge of cloud platforms, preferably Google Cloud Platform (GCP).
- 3+ years of hands-on experience in ML engineering or applied AI, including training and deploying models in production environments.
- Familiar with embeddings, prompt engineering and basic Retrieval Augmented Generation concepts.
- Experience fine-tuning and evaluating large language models (LLMs)—including families such as OpenAI (GPT), Anthropic (Claude), Google (Gemini), and open-source models like LLama, DeepSeek, Mistral, or Qwen—using techniques such as DPO, RLHF, or GRPO.
- Experience building multi-agent systems using orchestration frameworks like Langchain, CrewAI, LlamaIndex, among others.
- Language Proficiency: Professional proficiency in both English and Spanish to collaborate effectively in our bilingual environment 🗣️.
Nice to have ⭐
- Experience with advanced RAG setups and hybrid retrieval strategies, using multi-vector indexing or integrating graph-based data stores like Neo4j to enhance context and reasoning.
- Knowledge of LLM observability and guardrails, including tools like Arize, Confident AI (DeepEval), or Guardrails for prompt safety and hallucination filtering.
- Hands-on exposure to LLM red teaming, using frameworks like DeepTeam or PyRIT to test adversarial prompts and policy violations.
- Experience designing and implementing multi-agent LLM systems using protocols like MCP and A2A, along with a solid understanding of agent coordination patterns.
- Previous work in the financial or fintech space, or having worked in a banking or investment firm environment.
If this sounds like you, don’t worry if you don’t check every single box—we’ll support your growth along the way. 🚀🙌
What we offer 🎁
The hiring process ⚙️
- Send us your CV, cover letter, etc. 📧
- You’ll have a chat with our Head of People, Mireia Barón. 💬
- A meeting with our Head of AI, Héctor Borobia
- A technical discussion meeting with some of Flanks team members.
- Any extra meetings you (or we) might need to iron out any questions. 🤔
- We send you an offer! 💌
We aim to keep things moving fast—ideally wrapping things up in one to four weeks. ⏳💨
If this sounds like a good fit for you, we’d love to hear from you. Don’t hesitate to send us your CV and/or cover letter. ✉️🤗
At Flanks, we believe in fostering diversity and inclusion across everything we do. We’re proud to be an equal opportunity employer, and we welcome all applications regardless of race, religion, gender, age, or disability status. 🌈💼
Additionally, we have an Equality Plan in place to ensure fairness and inclusivity in all our policies and practices. 💙
- Department
- Tech
- Locations
- Barcelona Office
- Remote status
- Hybrid
About Flanks
Redefining the wealth management industry to make it simpler, seamless, and accessible to more people.
AI Gen & ML Engineer
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