Applied AI, Staff Engineer LOCATION: Worldwide (Remote-first / Hybrid optional) REPORTS-TO: AI Engineer, Lead Applied AI, Staff Engineer 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 now building the next generation of AI-enabled, modular, and intelligent software that infuses automation, reasoning, and context-aware assistance across our ecosystem. This role is a cornerstone in that transformation. About the Role As a Staff Engineer for Applied AI, you will design and build the systems that power CINC’s AI-native capabilities, from intelligent copilots and search assistants to reasoning-driven workflows across our platform. You will be a hands-on builder and technical thought leader, translating ideas into reliable, scalable systems that integrate large language models, orchestration frameworks, and cloud-native infrastructure. You will collaborate closely with Applied AI, Platform, and Product teams to accelerate the development of features that make complex work simpler and smarter for our users. This role is ideal for someone who combines strong engineering depth with product instincts, curiosity, and a collaborative mindset. Key Responsibilities - Design, develop, and maintain AI-powered backend services using TypeScript and Node.js, deployed on cloud-native infrastructure such as AWS, GCP, or Vercel
- Integrate large language models (LLMs) from providers like OpenAI, Anthropic, and Groq, optimizing for performance, reliability, and safety
- Build agentic systems using frameworks such as LangGraph, LangChain, or Semantic Kernel, with memory, tool use, and planning strategies
- Architect and maintain retrieval-augmented generation (RAG) pipelines and embedding stores using vector databases such as Weaviate, Pinecone, or Postgres pgvector
- Implement AI observability and evaluation using tools such as LangSmith, LangFuse, or Helicone to monitor performance, token usage, and user feedback
- Define API contracts and service boundaries for AI components that integrate seamlessly into CINC’s microservice and event-driven architecture
- Collaborate cross-functionally with Product, Design, and Engineering leadership to deliver chat interfaces, copilots, workflow assistants, and intelligent search
- Contribute to AI safety, governance, and compliance practices, including prompt injection prevention, PII handling, and cost optimization strategies
- Evaluate build versus buy options for AI and platform components, balancing speed, flexibility, and long-term maintainability
- Mentor engineers on AI integration, testing, and system design to raise the overall bar for AI craftsmanship
- Stay current with emerging LLM frameworks, open-source tools, and research to continuously improve architectural patterns and developer experience
Qualifications Core Technical Expertise - 8+ years of software engineering experience with deep fluency in Node.js and TypeScript
- Proven ability to design and deploy AI-first architectures that combine backend engineering with model orchestration
- Strong working knowledge of LangGraph, LangChain, or similar orchestration frameworks
- Experience integrating APIs from OpenAI, Anthropic, or Groq, and managing tokens, context windows, and streaming responses
- Familiarity with vector databases, semantic search, and embedding pipelines
- Solid understanding of API design, microservices, and system integration patterns
- Practical experience with cloud-native environments (AWS, GCP, or equivalent), including serverless compute and containerized deployments
Leadership and Collaboration - Demonstrated ability to lead through influence, setting technical direction and raising standards for quality and maintainability
- Skilled in communicating complex AI trade-offs and design decisions clearly to both technical and non-technical audiences
- Experience mentoring other engineers and contributing to architectural strategy
- Strong sense of ownership, curiosity, and ability to deliver in a fast-moving, global environment
- Strategic thinker capable of evaluating build versus buy decisions with long-term organizational impact in mind
- Preferred Experience
- Hands-on experience deploying AI-driven product features such as copilots, knowledge assistants, or intelligent search
- Experience with AI observability and evaluation frameworks such as LangSmith, LangFuse, Helicone, Ragas, or Promptfoo
- Exposure to Next.js, NestJS, or similar frameworks for backend and full-stack development
- Understanding of event-driven architectures, GraphQL APIs, or TypeScript-first API generation (Zod, tRPC)
- Prior contributions to open-source AI tooling or internal AI platforms
Mindset and Values - Builder’s mindset with comfort in ambiguity and a focus on delivering outcomes
- Clear communicator who can bridge technical and product conversations with credibility and empathy
- Learning-first attitude with curiosity about emerging models, frameworks, and best practices
- Values craftsmanship and continuous improvement in code quality, performance, and user experience
- Believes in collaboration, knowledge sharing, and elevating others through mentorship
What Success Looks Like - AI-powered features ship faster, with greater reliability and lower operational complexity
- Internal teams adopt shared AI patterns and tooling you help define
- Product and engineering teams view you as a trusted partner and technical leader
- CINC’s AI stack evolves with clarity, safety, and measurable impact for users
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