Senior AI Software Engineer

About the Role

We are seeking a Senior AI Software Engineer to design, build, and own production-grade AI capabilities across our proprietary SaaS CRM and LMS platform. This is a hands-on engineering role focused on delivering reliable, scalable AI-powered features that support real customer workflows. The role carries end-to-end ownership of AI-driven product functionality, from early technical design through deployment and long-term iteration.

You will design and implement AI services and workflows using modern machine learning and large language model tooling, working primarily in Python and LLM orchestration libraries such as LangChain or similar. The role involves selecting, evaluating, and applying models from leading providers such as OpenAI, Anthropic, and Google, as well as open-source model ecosystems, based on specific product use cases including speech-to-text and transcription, text-to-speech, conversational and task-driven LLM interactions, and retrieval-augmented generation (RAG). You will also design and operate AI service layers such as Model Context Protocol (MCP) servers, integrating these capabilities into backend services and collaborating with teams working in TypeScript (NestJS framework). This role requires strong architectural judgment and the ability to translate AI capabilities into production-ready systems that meet performance, reliability, and scalability requirements.

Reporting directly to the CTO and working closely with Product Management, this role emphasizes AI feature delivery, engineering excellence, and pragmatic execution. As a potentially remote position, we’re looking for an excellent, highly responsive communicator who is experienced and effective at collaborating in real time during core working hours. You should be able to quickly acknowledge requests, clearly communicate progress, and provide realistic time estimates for feature requests, helping align technical execution with product priorities. While Agile practices are used for much of the work, execution adapts to the needs of the product and customers.

What You’ll Do

• Build and operate AI systems that power customer engagement across voice, email, SMS, live chat, and web experiences, supporting both inbound and outbound communication workflows
• Develop AI-driven coaching functionality for our training program, The Closing Institute, including AI-based role-play, simulated patients, script and talk-track practice, and feedback on live calls and other real communication events
• Create marketing optimization capabilities that learn from real-world performance data to improve campaign effectiveness, conversion rates, and overall marketing outcomes over time
• Build AI-powered marketing content generation workflows that produce, adapt, and optimize messaging based on audience context, historical results, and business goals
• Implement and maintain AI services and workflows primarily in Python, selecting appropriate models, tooling, and architectures for each use case
• Design and operate AI service layers such as Model Context Protocol (MCP) servers, integrating AI capabilities into existing backend systems and product surfaces
• Work daily in GitHub using pull requests, code reviews, and branching workflows, contributing to CI/CD pipelines that build, test, and deploy AI services and supporting infrastructure
• Collaborate with Product Management and the CTO to plan work, make architectural decisions, and align AI development with product and platform priorities
• Integrate AI functionality with existing backend services in collaboration with teams working in TypeScript and Node.js (NestJS)
• Troubleshoot and resolve issues across AI services, backend systems, and supporting infrastructure in Windows and Linux environments
• Communicate technical progress, architectural tradeoffs, and delivery risks clearly to leadership and cross-functional partners

What We’re Looking For (Required)

• 7+ years of professional software engineering experience
• 2+ years of hands-on experience designing and implementing machine learning algorithms (MLA) or AI-driven systems in production environments
• Strong experience using Python to build AI services, automation, and data-driven product functionality
• Experience working with large language models and modern AI tooling, including model selection, prompt and workflow design, and integration with external model providers and APIs
• Ability and willingness to stay current with rapidly evolving AI models, tooling, and platform capabilities, and to evaluate new releases for practical product impact
• Experience with JavaScript and TypeScript and backend service development, including Node.js and NestJS, sufficient to integrate AI capabilities into existing systems
• Proven experience designing and implementing APIs and integrating with third-party systems in secure, scalable production environments
• Experience building and supporting SaaS or enterprise-grade software products with real users and uptime expectations
• Hands-on experience using GitHub for daily development, including version control, pull requests, and code reviews, and experience working within CI/CD pipelines and automated delivery workflows for production systems
• Experience working in Agile or Scrum-based environments, with comfort adapting execution and process as product needs evolve
• Ability to operate independently, take ownership of complex systems, and drive work to completion with minimal oversight
• Strong communication skills, with the ability to clearly convey technical progress, risks, and architectural tradeoffs to the CTO, CIO, Product Management, and Engineering teams

Nice to Haves

• Experience integrating with Dental Practice Management Systems such as Dentrix, Eaglesoft, OpenDental, Carestack, or other medical or healthcare-related systems
• Background working in healthcare or other regulated industries, with an understanding of compliance, data privacy, and operational constraints
• Experience building or operating AI systems involving voice, transcription, or conversational interfaces in production environments