Software Engineer - AI Experience *Remote* (m/f/d)

Das ist der Job

ABOUT US Pliant is a European fintech specializing in B2B payment solutions.

Darum lohnt es sich

Learn more at ABOUT THE TEAM Every company creates a messy trail of financial data: card transactions, invoices, receipts, merchants, budgets, approvals, policies, and exceptions. Our team is changing that. The AI Experience team builds AI-powered product experiences that help finance teams understand, automate, and optimize company spending.

ABOUT THE ROLE We are looking for an Applied AI Engineer to join the AI Experience team.

WHAT WE OFFER • The opportunity to work in a growing team with big responsibilities that thrives on a strong exchange of knowledge and excellence • Attractive remuneration • Your choice of preferred OS, Windows or Mac • Flat hierarchy and transparent communication in a relaxed, professional atmosphere • Opportunity to develop your talent in a dynamic team with ambitious goals • Flexibility and possibility to work remotely • Monthly mobility benefit • Wellhub Membership • Pliant Card with monthly credit to explore the product and enjoy food with colleagues Pliant is an equal opportunity employer.

Our modular, API-first platform helps businesses streamline spending, improve cash flow, and integrate payments into their financial workflows. Designed for industries with complex payment needs, such as travel and fleet, Pliant enables greater efficiency, control, and profitability.

We serve two primary customer segments: • Companies looking to optimize operational processes through intuitive apps and APIs, gaining control, automation, and financial flexibility through extended credit lines. • Businesses such as financial software platforms, ERP providers, and banks that want to launch or enhance their credit card offerings using Pliant's embedded finance and white-label solutions.

Founded in 2020 and headquartered in Berlin, Pliant supports over 4,000 businesses and more than 20 partners globally. As a licensed e-money institution (EMI), we issue credit cards in 11 currencies across more than 30 countries, helping companies streamline and simplify payments. Making sense of all of it is still far too manual.

That includes AI chat experiences, finance copilots, spend analytics, internal AI tooling, and autonomous workflows. This is not a prompt engineering role.

We build complex systems where LLMs are one component among many: structured financial data, APIs, retrieval, business logic, orchestration, evaluation, observability, and production infrastructure. We experiment a lot, but we care just as much about shipping. The goal is not to build impressive demos.

The goal is to turn promising AI capabilities into reliable product experiences customers can trust. You will work at the intersection of software engineering, product thinking, and applied AI. Some weeks, you might be prototyping a new finance copilot experience.

Other weeks, you might be improving how an agent reasons over transaction data, building evaluation pipelines, or making an AI workflow more reliable in production. You should be comfortable with ambiguity. We do not expect every problem to come with a clear spec.

Part of the role is figuring out what is worth building, what should be automated, where AI helps, and where traditional software is the better answer. If you enjoy exploring new AI capabilities but care deeply about turning them into reliable systems, this role should feel exciting.

WHAT YOU'LL DO • Design and build AI-powered product experiences for finance and spend management. • Build chat experiences, copilots, autonomous workflows, and internal AI tools that solve real customer and operational problems. • Work with LLMs, structured financial data, APIs, and business logic to build production-grade AI systems.

This includes retrieval systems such as vector search, hybrid retrieval, and text-to-SQL, plus OCR and document understanding. • Design AI solutions using the right approach for the problem; whether that’s tool calling, retrieval, agentic workflows, deterministic logic, or a combination of them. • Build systems that are observable and explainable, not black boxes.

Put guardrails and quality monitoring in place so we can trust them in production. • Create evaluation approaches that help us measure whether our AI systems are actually improving. • Experiment with new models and techniques, then turn the useful ones into production features. • Think carefully about accuracy, latency, cost, reliability, and user trust. • Collaborate closely with product managers, designers, and engineers to shape what we build. • Help raise the AI engineering bar across Pliant.

We welcome applications from people of all backgrounds, identities and abilities, and are committed to an inclusive hiring process. If you need any accommodations during the interview process, please let us know