AI Engineer Fintech Remote in Spain

About Tymit

At Tymit we were born on a mission to revolutionize creditmaking it smarter more flexible and always in the best interest of the customer.

We are embarking on a new phase to redefine payments and shopping experiencesgiving more to the customer. By bringing together financing loyalty and personalization driven by AI were creating a smarter and more rewarding way to shop. Fully funded by Frasers Group one of the largest retail groups in the UK we aspire to become a leading payment and shopping product in the UK market.

We believe credit should work for people not against them. Our technology is redefining how people shop pay and manage their spending. With teams across the UK and Spain we foster a culture of innovation collaboration and a customer-first mindset. As we scale we will partner with the UKs most prominent retail brands to deliver the most seamless and rewarding shopping experiences

Want to check our app from the guts See the Tymit app in actionhere!

Please note: this role is remote but must be based inSpain.

Compensation & Perks

• The salary range of this role is 50000 to 60000 euros depending on experience.
• 26 days of paid holiday plus bank holidays.
• Your birthday off.
• Private health insurance.
• Budget for home office set up.
• Monthly home working allowance.
• Tymit is working fully remote but we have offices in Madrid and London if your preference is to work from an office with other Tymiteers.
• Flexible working hours.
• Referral program.
• EUR 1000 annual learning and development budget.
• Length of service recognition program.
• Quarterly touchpoints to get together with the teams!

What Youll Do

• Ship AI features: Build production-ready LLM applications (RAG pipelines agents orchestration layers) that deliver real business impact.
• Ingest & normalize: Design and implement data ingestion and transformation pipelines for diverse inputs.
• Stand up retrieval: Implement and optimize vector databases (Qdrant Milvus Pinecone pgvector) define chunking/embedding strategies and improve retrieval quality.
• Orchestrate agents: Build and optimize multi-step agentic workflows using frameworks like LangChain/LangGraph Agno or CrewAI.
• Tune & optimize: Improve prompts fine-tune open-source models for specific use cases and optimize inference stacks for speed cost and reliability.
• Engineer context: Design and optimise context injection strategies (prompt templates retrieval augmentation dynamic context windows memory management) to improve quality reliability safety and cost-effectiveness of LLM responses.
• Observability & evals: Use tools like LangFuse LangSmith (or similar) to monitor pipelines run automated evals and track cost latency and quality.
• Secure the stack: Defend against prompt injection data leakage and unsafe outputs by implementing guardrails monitoring and escalation/fallback mechanisms.
• Collaborate: Work closely with Data and Product to identify opportunities and deliver high-value AI capabilities.
• Learn & adapt: Stay ahead of the curve in LLM orchestration observability security practices and emerging open-source frameworks.

What Were Looking For

• Proven experience shipping LLM-powered systems into production (not just demos).
• Strong software engineering background with fluency in Python (APIs data pipelines backend services).
• Hands-on experience with LangChain LangGraph Agno CrewAI or similar frameworks.
• Comfort with vector databases (Qdrant Milvus Pinecone pgvector).
• Experience integrating multiple LLM providers (OpenAI Anthropic Gemini AWS Bedrock and fine-tuned open-source models).
• Familiarity with observability tools (LangFuse LangSmith or similar) and designing evals for AI systems.
• Experience working on AWS cloud infrastructure.
• Deep interest in security: Awareness of LLM-specific threats (prompt injection data exfiltration malicious tool use) and strategies to mitigate them.
• Pragmatic startup-minded engineer: you deliver working systems quickly and iterate.
• We love engineers who tinker. If youve built your own AI tools played with agentic frameworks or contributed to open-source AI projects share it. Your GitHub tells us a lot about how you think.

Nice to have:

• Experience fine-tuning or hosting open-source LLMs.
• Contributions to open-source AI projects.
• Background in fintech retail or regulated industries.
• Experience with MLOps best practices (deployment monitoring CI/CD for ML).

What you can expect from our hiring process

Stage 1

45 min. video-call with our Tymits People team. Understand your career plan and what motivates you about Tymit.

Stage 2

45 min. video-call with one of the team. Technical discussion to understand more about the role and your skills.

Stage 3

90 min practical engineering session via video-call with other members of the team.
Pre-work will be set 48 hours before the session.

Stage 4

Offer!

To meet our regulatory obligations as a licensed financial services company in the UK Tymit needs to take background checks Criminal and Credit checks our new hires to help us safeguard our users. If you have any concerns regarding this process please discuss this with our People Team.

Tymit is made up of people from various backgrounds and you are welcome for who you are no matter where you come from what you look like. We seek to create a culture where everyone can belong because we believe that people do their best work to show up every day as their authentic selves. So bring us your personal experience your perspectives and your background.

We do not make hiring or employment decisions based on race religion age national origin gender gender identity or expression sexual orientation marital status disability pregnancy status or any other difference. If you have any disability please let us know whether there are any adjustments we can make for our process to be more inclusive.

Required Experience:

Manager