AI Engineer

Piano Overview 

Piano’s Digital Revenue Optimization solution helps digital services grow revenue by better understanding and influencing their customers’ behavior. Piano unifies analytics, segmentation, and commercial personalization in one AI-driven application, enabling sites and apps to efficiently maximize the value of every user visit. Headquartered in Amsterdam with offices in the Americas, Europe, and Asia-Pacific, Piano serves a global client base including the BBC, Deutsche Telekom, Nikkei, AXA and the Wall Street Journal.  For more information, visit piano.io. 

To help us achieve our ambitious goals, we are building cutting-edge solutions that go beyond traditional SaaS. At Piano, engineers and data scientists tackle complex technical challenges at scale, from architecting robust, globally distributed systems and developing powerful machine learning models that personalize user experiences in real time, to leveraging LLMs in production for a wide range of tasks to optimize all aspects of the company. Our team embrace a culture of innovation, collaboration, and craftsmanship where you’ll work with a modern tech stack and solve meaningful problems that impact millions of users worldwide. Join us to push technical boundaries, grow your skills, and be part of a team shaping the future of digital experiences. 

Position Overview 

The Data Science team at Piano is building an LLM-powered intelligence platform that transforms how we interact with customers and operate internally. At the center is our customer-facing chatbot—but the scope extends far beyond conversational AI. 

You'll work on systems that: 

• Power our customer-facing chatbot with state-of-the-art models from OpenAI and Anthropic 

• Collect, analyze and summarize conversational data to continuously improve customer interactions 

• Consolidate Piano's institutional knowledge into a unified platform that serves multiple teams 

• Deliver tailored LLM applications for Support, Client Success, Engineering and Executive teams—each with distinct analytical needs 

• Enable data-driven decisions through intelligent classification, summarization and insight extraction 

What makes this role unique: We need someone who can work across the full lifecycle of LLM applications—from context engineering and model integration to building the React interfaces where customers and internal teams interact with these capabilities. You'll leverage AI-assisted coding tools to move fast, but your familiarity with a wide range of techniques will be what makes you truly effective at shipping features and improvements. 

You'll collaborate withdata scientists and ML engineers on model selection, evaluation and optimization, Product and Design on crafting customer-facing features in exactly the right way and internal stakeholders to understand their needs for the LLM-based solutions you build. 

What you’ll do:

You'll join the LLM team, which builds and operates Piano's LLM-powered intelligence platform. This is a full-stack role where you'll work across the entire system—from RAG pipelines and LLM APIs to React frontends and middleware—shipping features that serve both customers and internal teams. 

Evolve our customer-facing chatbot 

• Build and refine the full stack: Python-based APIs that orchestrate RAG, call OpenAI/Anthropic models, and serve answers with low latency. 

• Implement frontend features and improvements in our React-based chatbot interface. 

• Develop middleware that connects conversational experiences to backend systems and data sources. 

Transform the chatbot into an agentic platform 

• Refactor the core engine to support tools and workflows—enabling the system to look up live data, execute actions, and make changes in Piano systems, not just answer questions. 

• Build and integrate AI agents across different business areas (Support, Client Success, Engineering, etc.) and connect them back to the chatbot as a unified control surface. 

• Design agent orchestration patterns that let users accomplish complex, multi-step tasks through natural conversation. 

Manage and leverage institutional knowledge 

• Build tools for effective knowledge management—ingesting, organizing, updating and versioning Piano's documentation, support content, and institutional expertise. 

• Create systems that ensure the right knowledge reaches the right LLM applications at the right time. 

• Monitor and improve retrieval quality through benchmarking and evals, as well as experimentation with embeddings, chunking strategies, and ranking algorithms. 

Reimagine Piano products with LLMs 

• Collaborate on ambitious initiatives to integrate AI capabilities into core Piano products, dramatically simplifying how customers configure and interact with our platform. 

• Build backend services and AI agents that tackle specific product challenges—turning complex workflows into intuitive, AI-assisted experiences. 

• Prototype, validate and productionize new AI-powered features that differentiate Piano in the market. 

Deliver production-grade systems 

• Deploy and operate services on Kubernetes with robust CI/CD pipelines. 

• Optimize LLM inference for cost and performance (context engineering, caching, model selection, batching). 

• Instrument, monitor and continuously improve reliability, latency and user satisfaction. 

Drive team excellence 

• Champion best practices in testing, code review and documentation across Python and React codebases. 

• Stay current with advances in agentic AI, RAG techniques and web technologies—bringing valuable innovations to the team. 

What we’re looking for:  

Must-have 

• 5+ years in software engineering, preferably building production ML or data-driven products. 

• Fluent in Python. 

• Experience with modern front-end tech (React or comparable). 

• Experience shipping and operating production ML/AI services (batch & real-time). 

• Cloud-native mindset: Docker, Kubernetes, observability, CI/CD, version control. 

• Strong engineering skillset with ability to create production-grade code. 

• Excellent communication in English; comfortable explaining trade-offs to both engineers and execs. 

Nice-to-have 

• Experience with vector databases, embeddings and retrieval-augmented generation. 

• Exposure to MLOps stacks. 

• Familiarity with analytics or personalization domains (propensity scoring, attribution, segmentation). 

• Understanding of JVM languages (Java) or Node.js back-ends. 

Education  

M.Sc. in Computer Science, Mathematics or related field, or alternatively a proven track record of delivering complex ML/AI-based systems in production. 

Why Piano 

• You enjoy being part of a forward-leaning tech company with high velocity. 

• You are motivated by the impact of building features that touch hundreds of global media brands and millions of end-users. 

• You prefer to choose your tools and to have influence over the tech stack. 

• You thrive among highly skilled peers collaborating across the globe. 

• We offer flexible working hours, competitive compensation and benefits. 

Keywords:

Generative AI, LLM, Python, Full-Stack, React, FastAPI, GraphQL, Pydantic AI, Hugging Face, PyTorch, fine-tuning, Kubernetes, Airflow, MLOps, Vector DBs, Docker, AWS, GCP, OpenAI, Anthropic. 

Applicants must have authorization to work in this jurisdiction without sponsorship from Piano.