Senior Full-Stack Software Engineer

LOCATION
:
Worldwide (Remote-first / Hybrid optional)

REPORTS-TO
: AI Engineer, Lead

CINC Systems

CINC Systems is the largest provider of accounting and management software in the community association management industry and the innovator behind accounting and banking integration. Founded in 2005 by a banker as the industry's first SaaS offering, CINC Systems now employs nearly 300 people and provides software and applications to more than 50,000 associations servicing over 5 million doors. In January of 2024, Hg Capital made a significant investment in CINC to accelerate the company’s growth trajectory and institute rapid product development.

We are modernizing our architecture, product, and engineering culture to build a new generation of AI‑enabled, modular, and intelligent SaaS applications. As a Senior Full Stack Engineer, you will play a key role in this transformation.

As a Senior Full Stack Engineer, you will design and deliver modern, scalable applications that connect deeply with our users and form part of a larger AI‑native platform. You will work across the stack, from backend services and APIs to responsive web applications and shared components.

This role is ideal for an experienced engineer who thrives in a fast‑moving, collaborative environment, values craftsmanship, and understands how to evolve large systems safely from monoliths to microservices. You will work closely with product, design, platform, and AI engineering teams to create software that is robust, maintainable, and forward‑looking.

• Design, build, and maintain high‑quality web applications using Type Script, Node.js, and frameworks such as React, Next.js, or NestJS
• Contribute to the evolution of CINC’s architecture from monolith to modular microservices, applying sound system design principles and domain‑driven thinking
• Develop and consume RESTful and Graph
  
  QL APIs with strong understanding of service boundaries, contract design, and versioning
• Implement event‑driven and message‑based integrations to improve scalability, resilience, and decoupling
• Apply modern engineering practices including automated testing, CI/CD, and continuous delivery principles
• Collaborate with design and product partners to translate complex requirements into simple, usable features
• Participate in code reviews, pair programming, and iterative delivery following Extreme Programming (XP) values
• Contribute to AI‑enabled workflows by integrating APIs or shared AI services into user‑facing features where appropriate
• Mentor and guide engineers on best practices in system design, testing, and clean code
• Engage in technical discussions around architecture, reliability, and performance to ensure quality and scalability across systems

• 7+ years of software engineering experience building production web applications or SaaS products
• Strong understanding of backend architecture, including monolith decomposition, microservice principles, and API design best practices
• Experience designing and maintaining RESTful or Graph
  
  QL APIs with clear contracts and documentation
• Knowledge of modern Dev Ops practices including CI/CD pipelines, observability, and containerised deployments
• Familiarity with cloud environments such as AWS, GCP, or Azure
• Solid experience with automated testing frameworks and test‑driven development (TDD)

• Excellent communicator who can clearly explain design choices and technical trade‑offs to engineers, product managers, and designers
• Demonstrated ability to take ownership of features from idea to deployment, balancing speed with quality
• Experienced working in cross‑functional teams and contributing to architectural discussions and reviews
• Learning‑first mindset with curiosity about new frameworks, design patterns, and AI‑driven development

• Experience integrating AI‑powered services such as chatbots, copilots, or search assistants
• Familiarity with LLM orchestration frameworks (Lang Chain, Lang Graph, or similar)
• Background in event‑driven architecture or streaming systems such as Kafka, SNS/SQS, or Pub/Sub
• Exposure to vector databases or…