Director, AI Product Development
CentralReach
Job Overview
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Job Description
About CentralReach
CentralReach is a leading provider of autism and IDD care software for Applied Behavior Analysis (ABA), multidisciplinary therapy, and special education. Trusted by more than 200,000 users, we enable therapy providers, educators, and employers to scale the way they deliver ABA and related therapies with innovative technology, market-leading industry expertise, and world-class customer satisfaction.
CentralReach’s AI team operates as an AI Foundry: a cross-functional group that rapidly builds, validates, and scales AI-enabled product capabilities. The Director, AI Product Development is the senior-most engineer on the AI team and sets the technical bar for how AI-powered product experiences are designed, built, evaluated, and operated.
This role is hands-on and deeply engaged across the early stages of development of AI applications, from early prototypes and pilots through production hardening and scale. They partner closely with AI product builders, Product organization leaders and DevOps to translate customer problems into reliable AI features that integrate seamlessly with CentralReach’s core workflows. They also establish engineering standards for AI application development: evaluation and quality thresholds, observability, guardrails and performance management.
Key Accountabilities
Technical Leadership & Engineering Excellence
- Serve as the technical lead for AI application development within the AI Foundry, setting standards for code quality, architecture, and delivery
- Lead by doing: design and implement core AI application components, critical services, and integration layers
- Mentor AI engineers; raise the bar on engineering rigor and AI-specific best practices
- Establish quality thresholds and release criteria (accuracy, latency, reliability, cost, and user trust)
- Design safeguards and “safe failure modes”: fallback behaviors, confidence thresholds, user controls, content filtering, and transparency patterns
AI Application Development (Hands-On)
- Build AI-powered product capabilities end-to-end (service + workflow integration + instrumentation), including LLM-enabled workflows, RAG, summarization, classification, and automation patterns
- Build and maintain shared libraries/components for AI application development (prompt/tooling patterns, service templates, evaluation utilities, safety layers)
- Own technical readiness for production: reliability, observability, performance tuning, and incident response preparedness
- Collaborate with platform Engineering and DevOps to ensure CI/CD and environment consistency, scaling strategies, cost controls for inference and secrets management and secure data handling
Cross-Functional Delivery & Integration
- Partner tightly with AI product builders and workflow Product owners to translate validated prototypes into production implementations
- Collaborate with core engineering teams to integrate AI capabilities into CentralReach’s main platforms
Strategic Direction & Innovation
- Identify and prioritize foundational investments that increase delivery velocity and reduce long-term maintenance: reusable components, platform primitives, and standardized patterns
- Evaluate build vs. buy decisions for AI tooling and recommend approaches aligned to CR constraints
- Stay current with AI application engineering practices and help translate emerging techniques into safe, valuable product capabilities
Desired Skills And Experience
- Bachelor's degree or equivalent work experience
- 10+ years of professional software engineering experience, with principal-level scope and demonstrated technical leadership
- Strong experience building and operating production distributed systems and backend services
- Demonstrated hands-on experience delivering AI/ML-powered product features (LLMs and/or traditional ML), including evaluation and monitoring
- Experience with retrieval systems and search relevance (RAG, embeddings, indexing, ranking, evaluation)
- Strong system design skills: APIs, data flows, integration patterns, performance and reliability tradeoffs
- Experience with observability and operational excellence (logging, metrics, tracing, alerting, incident response)
- Ability to communicate technical concepts clearly to product, design, and executive stakeholders
- Experience in a healthcare SaaS environment
- Familiarity with multi-tenant architectures and enterprise access control models
- Experience building internal platforms/tooling that improve developer experience and standardize best practices
Compensation & Benefits
Base Salary Range: $180,000—$200,000 USD
Backed by Roper Technologies, Inc. (Nasdaq: ROP), and led by award-winning CEO Chris Sullens, CentralReach is entering an exciting phase of growth, innovation, and scale.
Recognized as one of the best places to work over 10 times by organizations such as Inc, Built In, and NJBIZ, our culture is centered around impact, inclusion, and flexibility. As a hybrid company with collaborative offices in Ft. Lauderdale, FL; Holmdel, NJ; and Verona, Italy, we foster a workplace where top talent can thrive and make a real difference in the lives of those we serve.
We offer competitive compensation, comprehensive health benefits, generous PTO, 401(k) matching, and paid parental leave. Our team members also enjoy hybrid work schedules, career development support, wellness programs, and opportunities to give back through CR Cares™, our community engagement initiative.
Be part of a market leader driving the future of care. Explore opportunities at centralreach.com/careers.
Key skills/competency
- AI
- Machine Learning
- Distributed Systems
- Product Development
- Software Engineering
- LLMs
- RAG
- System Design
- DevOps
- Observability
How to Get Hired at CentralReach
- Research CentralReach's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Customize your resume to highlight experience in AI product development, distributed systems, and healthcare SaaS.
- Showcase technical leadership: Prepare to discuss your experience in setting engineering standards and mentoring AI engineers.
- Demonstrate AI application expertise: Be ready to present projects involving LLMs, RAG, and productionizing AI features.
- Highlight problem-solving skills: Focus on examples where you've translated customer problems into reliable AI solutions.
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