Sr. SWE HOAi Voice

Description

HOAi is a fast-growing startup revolutionizing the community association management industry. Our AI workforce platform integrates machine learning technology to streamline labor-heavy processes, eliminating inefficiencies and driving scalability. With rapid growth in the AI space, we are pushing boundaries to redefine industry standards. 
HOAi is the leading AI solution for the community association management industry, enabling organizations to deploy AI Agents that function like experienced managers. These AI Agents go beyond traditional AI by proactively executing complex, multi-step processes with human-like reasoning—working autonomously, 24/7, across your entire operation. This transformation optimizes labor costs, enables growth without additional hires, and ensures faster, higher-quality service for residents and board members. HOAi was acquired by Vantaca in the fall of 2024. Vantaca just achieved unicorn status with a $1.25B valuation, so it's safe to say we're past the "scrappy startup phase." We're not just building a successful company – we're building the category-defining platform that will transform how an entire industry operates.  
Here's the reality of our trajectory: 

• Growing 100% year-over-year 
• Our AI product (HOAi) went from $0 to millions in months 
• Backed by Cove Hill Partners and JMI Private Equity 
• 6M+ doors on our platform, displacing legacy systems 

Overview
As a Senior Software Engineer focused on HOAi Voice, you will be at the forefront of building and scaling Vantaca's conversational AI platform that transforms how community associations interact with residents. You'll design and develop production voice AI systems that handle thousands of conversations across voice, SMS, and webchat, integrating natural language processing with our community management platform to automate service requests, answer resident questions, and provide 24/7 support. This role requires deep expertise in conversational AI, telephony integration, and production ML systems, combined with a passion for creating seamless user experiences that make complex community management workflows accessible through natural conversation.  
Success Metrics
Within the first 6-12 months, success in this role will be measured by: 

• Conversation Quality: Achieve 85%+ intent recognition accuracy and 80%+ successful conversation completion rates without human intervention. 
• System Reliability: Maintain 99.5%+ uptime for voice AI systems with average response latency under 2 seconds. 
• Scale & Performance: Successfully deploy systems handling 10,000+ monthly conversations with consistent quality as volume grows. 
• User Satisfaction: Achieve Net Promoter Score (NPS) of 40+ for AI-assisted interactions and user satisfaction ratings above 4/5. 
• Operational Efficiency: Reduce human handoff rates to under 20% through improved AI accuracy and conversation design. 
• Feature Delivery: Ship production-ready features and improvements on schedule while maintaining code quality and test coverage standards. 
• AI Safety & Quality: Implement monitoring systems that detect and prevent hallucinations, maintain response accuracy above 90%, and ensure appropriate escalation protocols. 
• Team Impact: Contribute to technical documentation, establish best practices for conversational AI development, and mentor team members on ML/NLP approaches. 

Responsibilities

• Design, build, and deploy production-grade conversational AI systems that handle multi-turn dialogues across voice (telephony/IVR), SMS, and webchat channels with consistent user experiences. 
• Develop and optimize natural language processing pipelines for intent classification, entity extraction, and context management in domain-specific community management scenarios (service requests, violation reporting, amenity reservations, payment inquiries). 
• Integrate voice AI systems with telephony platforms (Zoom, RingCentral, Microsoft Teams) and conversational AI frameworks (Dialogflow, Amazon Lex, Rasa, or similar) to enable real-time, low-latency conversation handling. 
• Implement retrieval-augmented generation (RAG) systems that connect large language models with Vantaca's knowledge base and external APIs, enabling the AI to access real-time community data, work orders, and property information. 
• Build and optimize LLM-powered conversation flows using advanced prompt engineering techniques, ensuring accurate, contextually appropriate responses while mitigating hallucinations and maintaining AI safety standards. 
• Design robust fallback mechanisms, human handoff protocols, and escalation workflows to ensure seamless transitions when AI confidence is low or situations require human intervention. 
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