Senior Software Engineer - AI Team

Senior Software Engineer - AI Team

is the AI-powered platform that helps client-services organisations deliver work profitably. From project management and resource planning to time tracking and financial oversight, we give agencies, consultancies, and professional services teams everything they need to stay organised, run efficiently, and protect their margins. Our mission is to make every team that delivers client work more productive and more profitable — and we’re building AI into every layer of the platform to make that happen.

This is a remote employment contract role in Poland only.

The AI Team is a specialist enabling team at the heart of how Teamwork builds intelligent product. We’re responsible for the infrastructure, frameworks, and engineering capabilities that every product team depends on to ship AI-powered features and workflows. We don’t just build AI — we make it possible for the entire engineering organisation to build with AI confidently, consistently, and  you want to shape the foundations that a whole product is built on, this is the team.

• Design, build, and maintain the core AI infrastructure, frameworks, and shared services that product teams across Teamwork rely on to deliver AI-powered features
• Develop and evolve APIs, SDKs, and integration patterns that make it straightforward for teams to embed AI capabilities into their product areas
• Build and maintain evaluation frameworks (evals, benchmarks, quality metrics) that give teams confidence in AI feature quality before and after release
• Work across backend (Node/Go) and frontend (Vue
  3) where needed, with a primary focus on backend systems, data pipelines, and AI service layers
• Collaborate with product teams to understand their AI needs, unblock adoption, and ensure the platform capabilities evolve alongside product requirements
• Work with LLM providers, embedding models, vector stores, and retrieval pipelines — selecting, integrating, and optimising the right tools for each use case
• Bring AI features to production, instrument them for real-world performance, and iterate based on customer feedback and usage data
• Use AI tools throughout your own development workflow to accelerate delivery, improve quality, and reduce manual effort
• Contribute to engineering culture by documenting patterns, sharing best practices, and raising the AI capability of the wider engineering team
• Continuously improve how we build and ship AI — optimising for reliability, quality, speed, and customer impact

• Strong experience building and shipping AI-powered product features in a production environment — not just prototypes, but features that real customers use and that have been improved based on their feedback
• Backend expertise in one of Node, Go, Python, or a similar language, with experience building scalable APIs and services
• Hands‑on experience working with LLMs, prompt engineering, retrieval‑augmented generation (RAG), embeddings, or similar AI/ML techniques in a product context
• Experience designing and running evaluations (evals) to measure AI feature quality, accuracy, and reliability — and using those results to drive improvement
• Solid experience with cloud infrastructure and distributed systems on AWS or similar (containers, managed databases, message queues, search)
• Familiarity with modern JavaScript frameworks (Vue, React, or similar) — enough to contribute to frontend work when needed, even if backend is your primary strength
• Demonstrated, active use of AI tools (e.g. Claude, Copilot, Cursor, or similar) to improve how you work across the development lifecycle
• Experience working in cross‑functional or platform/enablement teams, building tools and capabilities that other engineers depend on

• Strong product mindset — you understand that AI infrastructure exists to serve product outcomes, and you make decisions that balance technical rigour with customer and business impact
• Ability to critically evaluate AI outputs, design effective prompts and pipelines, and build systems that degrade gracefully when models behave unexpectedly
• A sharp eye for AI quality — you know how to define what “good” looks like for an AI…