Senior Backend Engineer 3

About Dentira
Dentira is one of the fastest-growing, Series B, profitable healthcare technology companies, building the next generation infrastructure for clinic operations. We started by revolutionizing dental procurement with the world’s first real-time price and product comparison engine for dental supplies. Today, Dentira operates across the US, Canada, Asia Pacific, and Europe. Building on this foundation, our Lab Platform streamlines case creation and management by connecting clinics, intraoral scanners, and dental labs. We’re also applying AI to complex healthcare problems such as automatic invoice reconciliation, procedure cost prediction, and intelligent procurement, with solutions that have broad applicability across healthcare. As we expand into adjacent verticals, our goal is to achieve 10X growth over the next 3 years and be at the forefront of Agentic Commerce for healthcare supplies. Dentira just raised a $50M Series B from Vista Equity Partners, one of the world's leading technology-focused private equity firms and an investor behind landmark software transactions including the $16.5B acquisition of Citrix.
The Role
We’re looking for a Senior Backend Engineer with 5+ years of experience building performant, scalable, and reliable systems at product companies and startups.You’ll work on challenging engineering problems spanning distributed systems, data-intensive platforms, event-driven architectures, APIs, AI-powered workflows, and high-scale backend infrastructure that directly power healthcare operations across multiple markets. This is a high-ownership role.
You’ll take complex and often ambiguous problems from requirements and architecture through implementation, production deployment, observability, scaling, and incident resolution.
We’re looking for someone with strong problem-solving fundamentals who can use the right abstractions to turn complex real-world problems into elegant, maintainable systems. You should be comfortable operating in a fast-paced environment with changing priorities and influencing technical decisions beyond your immediate area of ownership.
You should also be AI-native in how you engineer - comfortable using coding agents, LLM-powered development workflows,and agentic practices to accelerate implementation, debugging, testing, and system understanding.
Primary Requirements
5+ years of experience building and scaling backend services and microservices using Nodejs (with TypeScript) and Go.
Strong expertise in API design best practices across REST and GraphQL, with a solid understanding of HTTP fundamentals, API contracts, versioning, reliability, and performance.
Deep experience with SQL and NoSQL databases, including PostgreSQL and MongoDB, with expertise in database design, query optimization, indexing, and operating databases at scale.
Strong data modelling skills, with the ability to design schemas and domain models that remain maintainable as products and requirements evolve.
Strong ability to use abstractions effectively - designing clean interfaces, reusable components, and well-defined system boundaries without unnecessary complexity.
Strong hands-on experience with event-driven architectures and distributed systems, including message brokers such as RabbitMQ or Kafka, with the ability to design for scalability, resilience, consistency, and reliability.
Hands-on experience with Docker and Kubernetes, including deploying, operating, troubleshooting, and scaling production workloads.
Strong understanding of backend system performance, concurrency, caching, asynchronous processing, fault tolerance, observability, and production reliability.
End-to-end ownership of backend systems - from requirement clarification and architecture design through implementation, production deployment, monitoring, scaling, and incident resolution.
Solid foundation in data structures and algorithms, coupled with strong debugging and troubleshooting skills.
Experience mentoring engineers, conducting thoughtful code and architecture reviews, and influencing engineering standards and technical best practices.
An AI-native engineering mindset, with demonstrated ability to effectively use coding agents and agentic development practices to accelerate development, debugging, testing, and problem-solving.
Good to Have
Experience designing or operating LLM-powered production systems, especially where correctness matters
Worked with agent orchestration frameworks, or with MCP and the surrounding ecosystem
Open-source contributions or meaningful participation in developer communities.

Work arrangement
No