Role Description You'll own Pling's architecture and code, strategy and execution. The role is hands-on and impact-driven: you contribute to product discussions alongside the founders, then own the full technical lifecycle — architecture, implementation, deployment, monitoring, and continuous improvement in production — with a focus on real-world reliability and business impact. Your mandate is to architect and ship the platform that takes Pling to the next 10x of customers and locations — AI-native by design, built to scale across multi-site groups across Europe — and to build the development pipeline that makes our shipping velocity hard to match. We believe a small, AI-augmented engineering team can outship teams five times its size. You'll prove that with us. What you'll do - Build complete features end-to-end — data model to API to UI - Own the technical direction — architecture, infrastructure, security, performance - Design and own the LLM pipelines that power Pling's AI features — prompt design, structured outputs, evals, monitoring, cost tracking - Set engineering standards across code and AI features — testing, CI/CD, observability, code review on one side; eval harnesses, regression checks, and quality metrics tied to business outcomes on the other - Define and lead the migration to our next-generation architecture — the stack choices are yours to shape - Build the development pipeline that makes our shipping velocity hard to match - Hire and lead — bring on the next engineer when the time is right, and define how the team works Qualifications - 6–9+ years building production software in fast-paced environments, with at least 2 years focused on LLM-powered features in production - Pragmatic about architecture and tradeoffs; you've learned that good engineering usually means removing complexity, not adding it - Comfort across the stack — backend center of gravity, but able to ship end-to-end - Production experience with Python, TypeScript/Node.js, and modern databases (SQL and NoSQL) - AI-native fluency - Deep practical understanding of LLM behavior: prompting, structured outputs, context window management, common failure modes, handling non-determinism, and writing evals that catch regressions before users do - Pragmatic about model selection — pick across providers (Claude, GPT, Gemini, open-weights) based on cost, latency, and quality tradeoffs for each use case - Know when not to reach for an LLM. A lot of good engineering is knowing when a regex, a lookup table, or deterministic code is the right answer. You hate AI slop as much as you love AI leverage. - Follow the field actively and adopt new tools when they earn it. Requirements - Builder mindset — you'd rather build than manage. AI excites you because it lets you ship at a scale you couldn't before. - Engineering excellence — code quality is a habit, not an afterthought: testing, review, quality gates - Strong on operational excellence: security, reliability, performance, observability - Confident with CI/CD and production deployments Collaboration - Clear communicator who explains technical trade-offs to founders, customers, and future hires - Balance speed, quality, and long-term sustainability in your decisions - Fluent English. German is a big plus — our customers operate in German Benefits - Strong traction in an attractive niche. - Profitable, growing fast, in a category few others are addressing. - An ambitious platform vision. - Horizontal expansion to other medical specialties and a vertical marketplace dimension both within reach. - Equity anchored at pre-fundraise valuation. - Dynamic, fast-paced environment with experienced founder-operators and domain experts — direct access, fast decisions. - AI-native team — everyone at Pling uses AI as a daily tool. - Remote-first today with regular team meetups in Berlin. Hybrid options as we open offices. - 30 days of PTO. Company Description Pling versetzt Zahnarztpraxen in den Autopiloten. Unsere KI-gestützte Plattform vereint Geräteverwaltung, Service-Tickets, Aufgaben und QM in einer App, erstellt Hygiene- und Wartungspläne selbst und erinnert zuverlässig an Fristen. So sparen Teams wöchentlich Stunden, vermeiden Technikereinsätze und bestehen jede Begehung gelassen – mehr Zeit für Patienten statt Papierkram. Pling puts dental practices on autopilot. The AI-driven platform combines device management, service tickets, task schedules and compliance in one app, auto-generates hygiene and maintenance plans and never lets deadlines slip. Teams save hours every week, cut engineer call-outs and sail through inspections – freeing them to focus on patient care, not paperwork.

• Responsible for delivering secure, high-performance applications and services • Support the full software development lifecycle—from analysis and design through implementation, testing, and deployment • Modernize and integrate legacy systems with cloud-first, full-stack solutions • Collaborate with the Technology Team to deliver solutions

Role Description We are looking for a Senior Full Stack Engineer to join our dynamic R&D Team, where you will own high-scale features end-to-end across our FinOps platform and AWS billing engine — contributing directly to our mission of empowering fast-paced startups. This is an agentic engineering role. It is not a traditional coding role. You will generate the vast majority of your production code with AI, and your value comes from the deep technical judgment you apply on top of it: guiding the model, critiquing its output, and shipping solutions that are high-quality, maintainable, and future-proof. We’re looking for someone excited that the craft of software is changing, and who wants to operate at (and help define) the frontier of it. You will work with: Node.js/TypeScript (NestJS, Fastify, Prisma ORM) + React (TanStack, TipTap, Material UI, Untitled UI) + PostgreSQL. 📍 Work location: remote from Ukraine If you are interested in this opportunity, please submit your CV in English. Key Responsibilities - Own features end-to-end — from vague stakeholder ask to production deployment, including discovery, design, implementation, testing, rollout, and iteration. - Refine requirements proactively using the Value, Usability, Feasibility, Viability (VUFV) framework. - Generate your code with AI (we provide top-tier AI tooling — currently Claude Opus 4.7 in Cursor). - Build and evolve our AI workflow — don’t just use it. - Solve deep technical problems across FinOps processes and AWS billing calculations. - Ship scalable, maintainable, well-tested, well-documented code. Qualifications - 5+ years of experience as a Full Stack Engineer shipping production systems. - Deep expertise in the TypeScript full-stack ecosystem — specifically NestJS and React. - Strong experience with Prisma ORM + PostgreSQL. - Strong debugging skills and a serious approach to unit testing. - Proven ability to translate complex, ambiguous business requirements into concrete technical specs and actionable work. - Excellent problem-solving skills and a bias toward action and unblocking. - Agentic engineer. AI is your primary authoring tool. - AI workflow contributor. You don’t just consume the AI setup we have — you improve it. - Fluent written and verbal English. Nice to have - Experience with vector databases. - Experience with monorepo tooling (Turborepo, Nx). - Familiarity with AWS services, especially AWS Cost Explorer and AWS Cognito. - Experience with financial dashboards or data-heavy UI. - Strapi Framework experience. - Experience with Material UI at scale. - Strong SQL knowledge. - Experience with Puppeteer / Playwright. - Experience with Fastify. What Success Looks Like in Year One - Agentic delivery is your default. - You’re the go-to mind on the AWS billing engine. - You turn vague asks into the right product. - You’ve delivered real end-to-end features on the stack. - You’ve raised the team’s AI bar. Benefits - Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.). - International work environment. - Referral program – enjoy cooperation with your colleagues and get a bonus. - Company events and social gatherings (happy hours, team events, knowledge sharing, etc.). - English classes. - Soft skills training. - Country-specific benefits will be discussed during the hiring process.

• Become a key contributor in the backend development for 3D AutoReview features, from pipeline architecture to production delivery • Experiment with geometry parsing, quality detection, and context generation for 3D model review • Partner with backend, frontend, and product teams to drive the delivery of high-impact features with speed, quality, and cross-functional alignment. • Collaborate with ML teams to incorporate intelligence into the 3D review process • Develop extensible systems for custom rule creation and reference data in 3D AutoReview • Help set and maintain high technical standards across the team