Senior Applied AI Engineer

Title: Senior Applied AI Engineer

Location:

Worldwide (Remote/Hybrid) 
Reports to: Staff Applied AI Engineer

 

Senior Applied AI Engineer 

 

About 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 400 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.

 

At CINC, innovation drives our growth, and our people sustain it. We are proud of our humble, accountable, and team-oriented culture, and we are committed to building products and a workplace that create long term value for our customers and our team.

 

About the Role 

The Senior Applied AI Engineer is a hands-on software engineer specializing in the practical application of AI within production systems. This role sits at the intersection of software engineering, system design, and applied machine learning, with a focus on building AI-enabled features that are observable, testable, and safe. 

 

This is not a research role. It is a product- and systems-oriented role for an engineer who understands that AI is an amplifier of engineering fundamentals and who can balance experimentation with operational discipline. 

 

Key Responsibilities 

• Design, build, and operate AI-enabled features within production SaaS applications 

• Integrate large language models and other ML capabilities into existing systems with attention to reliability, latency, and cost 

• Design AI workflows including retrieval, orchestration, evaluation, and fallback strategies 

• Partner with product and design teams to translate user needs into intelligent system behavior 

• Collaborate with platform and DevSecOps teams to ensure AI systems are secure, observable, and scalable 

• Build evaluation strategies to measure quality, regressions, and business impact of AI features 

• Contribute to system and service design to ensure AI capabilities fit cleanly into overall architecture 

• Apply strong software engineering practices including testing, code review, and incremental delivery 

• Mentor other engineers and share best practices for applied AI development 

• Stay current with evolving AI tools and techniques, applying them pragmatically where they add value 

Qualifications 

Technical Expertise 

• 8+ years of professional software engineering experience 

• Hands-on experience building and shipping AI-enabled features in production 

• Strong foundation in system design, APIs, and distributed systems 

• Experience working with LLMs and other ML models  

• Familiarity with evaluation, monitoring, and observability of AI workflows 

• Experience with cloud-native architectures and managed cloud services 

• Comfort working across backend services, data pipelines, and user-facing systems 

Collaboration and Judgment 

• Strong communication skills, able to explain AI trade-offs clearly 

• Structured thinker with good engineering judgment 

• Comfortable operating in ambiguity and iterating based on feedback 

• Ability to work cross-functionally with product, platform, and data teams 

• Bias toward shipping value safely and incrementally 

Mindset and Values 

• Builder mindset with pride in reliable, maintainable software 

• Believes AI amplifies both good and bad engineering practices 

• Customer-focused, measuring success through real-world impact 

• Learning-first attitude and intellectual humility 

• Calm under pressure and disciplined in execution 

• Values teamwork and shared ownership 

What Success Looks Like 

• AI-enabled features deliver measurable customer and business value 

• AI systems are reliable, observable, and cost-effective 

• Engineering teams can safely build on shared AI patterns and infrastructure 

• AI experimentation leads to production outcomes, not dead ends 

• The Senior Applied AI Engineer is trusted as a practical expert and partner across teams