Dentistry Automation
Website:
dentistryautomation.com
Job details:
Company Description
Dentistry Automation offers an innovative platform that streamlines dental practice operations by automating routine tasks, improving workflow efficiency by up to 70%, and optimizing revenue cycle management by 80%. Our system provides real-time insights into practice performance through intuitive dashboards and reports, all accessible via a user-friendly interface. Key features include seamless PMS integration through our DentalBridge API, instant insurance eligibility verification, and robust tools for monitoring financial health and operational metrics. We are committed to simplifying dental practice management and empowering teams with smart, cloud-based solutions.
Experience - 3-5y
We’re looking for a strong Python engineer who wants to work close to the product, build AI-enabled workflows, own meaningful parts of the codebase, and grow into a trusted engineering partner over time.
You’ll be joining an existing product built by a senior engineer with deep experience across machine learning, product, and startup engineering. The codebase already has a strong foundation, and the next phase is about making the product more reliable, scalable, polished, and easier to evolve, while expanding the use of AI agents and automations across key workflows.
This role is ideal for someone who enjoys building real product features, improving systems thoughtfully, and applying AI in practical, production-oriented ways.
You’ll start by shipping well-scoped improvements, tightening existing workflows, improving reliability, fixing edge cases, and building backend/product features. As you develop deeper context, you’ll gradually take ownership of larger workflows, core parts of the system, and AI-assisted automation flows.
You’ll work closely with the founding/senior engineer, who will continue leading product direction, architecture, AI strategy, and new bets. This is a strong opportunity for someone who wants mentorship, autonomy, and a clear path toward deeper product, technical, and AI-system ownership.
What you will work on -
You will:
- Build and improve backend features using Python.
- Design, build, and improve AI agent automations that support real product workflows.
- Work on LLM-powered features, agentic workflows, tool-calling flows, structured outputs, and backend integrations.
- Own small to medium-sized product improvements from implementation to release.
- Improve APIs, internal tools, data flows, and backend workflows.
- Debug issues, handle edge cases, and improve product reliability.
- Improve reliability and observability of AI-driven workflows, including fallbacks, retries, logging, and evaluation loops.
- Write clean, maintainable code that fits the existing architecture.
- Add tests, documentation, and internal tooling where it helps the system move faster.
- Gradually take ownership of recurring engineering areas, product workflows, and AI automation surfaces.
- Work closely with product and engineering decisions, not just isolated tickets.
What we are looking for -
You should have:
- 3 to 5 years of hands-on backend or full-stack engineering experience.
- Strong Python fundamentals.
- Experience building AI agents, LLM-powered workflows, or AI automations in a product or internal-tools context.
- Practical familiarity with concepts such as tool calling, prompt design, structured outputs, RAG, workflow orchestration, evals, retries, and guardrails.
- Good software design instincts.
- Comfort working in an existing codebase and making careful, high-quality changes.
- The ability to understand product requirements and translate them into practical engineering work.
- Strong debugging habits and attention to detail.
- A bias toward simple, reliable, maintainable solutions.
- Interest in growing into deeper ownership of systems, workflows, AI automations, and product areas.
Why this role is interesting -
This is not a role where you’ll only pick up random tickets.
You’ll become one of the key engineers responsible for making the product stronger, smoother, more scalable, and more AI-native. You’ll get to understand how the system works end to end, improve it steadily, and grow into owning important parts of the product independently.
You’ll work close to product, learn directly from a senior engineer/founder profile, and get the space to build both technical depth and product judgment. You’ll also get hands-on exposure to practical AI engineering: not demos or toy agents, but production workflows where reliability, user experience, and business outcomes matter.
This is a good fit for someone who wants to move beyond task execution and grow into a dependable product-minded engineer who can own real outcomes across backend systems and AI-powered workflows.
Side Note - If you're applying, please send us your Github ID.
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