The Role
Own Pling’s technical direction and deliver end-to-end production features across architecture, backend, APIs, UI, infrastructure, security, deployment, and monitoring. Design and operate LLM pipelines, evaluations, quality controls, and cost monitoring. Lead architectural migration, engineering standards, CI/CD, observability, and agentic-AI practices. As the team grows, hire and guide engineers while balancing speed, reliability, performance, and maintainability.
Summary Generated by Built In
About Pling
The team
The role
What you’ll do
About you
Why Pling
Pling builds the operational backbone for medical practices, starting in dentistry. Most dental software handles the patient journey (documentation, treatment plans, billing) — we handle the operations enabling it: equipment management, regulatory compliance, team coordination, service procurement — a segment the wider industry has largely overlooked. Our vision: expand horizontally into other medical specialties and vertically into a marketplace connecting practices with manufacturers, technicians, and service providers.
- Six-digit ARR, 90%+ gross margins, growing ~4x year over year
- Proven product-market fit with a diverse customer base — from single practitioners to enterprise-level dental chains
- Bootstrapped by design — profitable, growing without external capital, raising our first round in Q4/Q1
- Sticky by design — compliance obligations make Pling mission-critical infrastructure; once integrated, customers don’t churn
The team
The founding team combines deep startup, product, and domain expertise.
- Paolo (CEO) — Stanford-educated, spent 8 years in Silicon Valley where he built and sold a startup, ex-BCG, two prior exits
- Henrik (CPO) — ex-BCG, N26, ImmoScout24, early-stage startups
- Jonas (CMO) — former clinician at Uniklinik Düsseldorf, ran his own practice, self-taught engineer. Currently owns Pling’s technical architecture and codes alongside the team.
The role
You’ll own Pling’s technical domain — 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
- Build the team’s agentic-AI practice — the shared conventions, review patterns, and guardrails that let a small AI-augmented team ship reliably and scale without drowning in AI slop
- Hire and lead — bring on the next engineer when the time is right, and define how the team works
About you
Experience
- 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.
- Proven at team scale, not just solo — you’ve established how a team works with agentic AI: shared conventions, code review calibrated to AI-generated logic, and eval expectations that keep output reliable as the team grows
Builder mindset
- You’d rather build than manage. AI excites you because it lets you ship at a scale you couldn’t before.
- High agency: you operate independently in fast-changing conditions and don’t wait for permission to solve the problem in front of you.
- You love writing and shipping code — and you’re not precious about it. When the problem shifts, you rewrite rather than defend.
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
Why Pling
- 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. Because we haven’t raised yet, the upside on equity granted now is materially higher than it will be even six months from now.
- Dynamic, fast-paced environment with experienced founder-operators and domain experts — direct access, fast decisions.
Skills Required
- 6–9+ years building production software in fast-paced environments
- At least 2 years of experience building LLM-powered features in production
- Production experience with Python
- Production experience with TypeScript and Node.js
- Production experience with modern SQL and NoSQL databases
- Comfort working across the stack, with a backend focus
- Pragmatic architecture and engineering tradeoff judgment
- Practical expertise with prompting, structured outputs, context windows, LLM failure modes, nondeterminism, and evaluations
- Experience selecting and operating models across providers based on cost, latency, and quality
- Experience establishing team conventions and review practices for agentic AI
- Strong testing, code review, quality gates, security, reliability, performance, and observability practices
- Confidence with CI/CD and production deployments
- Clear communication with founders, customers, and future hires
- Fluent English
- German language proficiency
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The Company
What We Do
Pling builds the operational backbone for medical practices, initially targeting dentistry. Its platform combines device management, service tickets, tasks, quality management, regulatory compliance, and service procurement in one workflow. It creates hygiene and maintenance plans, reminds teams about deadlines, reduces administrative work and technician call-outs, and helps practices stay inspection-ready. Pling plans to expand across medical specialties and connect practices with suppliers and service providers.
