Role Description GeminiSense is looking for an Agent Builder, someone who can design, build, and ship AI agent systems that either transform how our company operates or become standalone products our customers pay for. This is not a research role. You will be embedded directly inside GeminiSense, working alongside their teams, understanding their operations, and building AI agents that handle real work: customer service, sales outreach, onboarding, documentation, and more. Some of what you build will replace manual workflows within those companies. Some of it will become new revenue-generating products sold to their customer bases. Either way, it ships to real users. What You'll Do - Build Internal AI Agent Teams: - Design and deploy AI agents that handle operational work across GeminiSense, including customer support tiers 1 and 2, SDR and sales outreach, onboarding automation, content and marketing workflows, and engineering maintenance. - Measure impact in hours of labor replaced or team output increased. - Work directly with portfolio company operators to identify the highest value automation opportunities. - Build External AI Products: - Develop new AI powered products such as vertical voice agents, AI copilots, workflow automation tools, and AI documentation systems tailored to our industry. - Own the product from prototype through launch, including reaching first paying customers. - Ship and Iterate: - Move fast from idea to MVP to production. - Run beta tests with real users, gather feedback, and improve continuously. - Collaborate cross-functionally with product, engineering, and go-to-market teams. Qualifications - Proven track record of building products, tools, projects, startups, or side projects that went live. - Strong working knowledge of AI and machine learning tools, large language models, and agent frameworks. - Ability to go from zero to functional prototype quickly. - Comfort with ambiguity. You will often be defining the problem as much as the solution. - Bias toward action over planning. Nice to Have - Experience building AI agents, voice agents, or workflow automation. - Background in vertical SaaS or B2B product development. - Familiarity with the security industry. - Previous startup or founder experience. - Experience working across multiple product lines or business units. Benefits - Health coverage. - A dedicated building budget for APIs, tools, and infrastructure. Compensation - Base Salary: Competitive. - Variable Compensation: High-upside, performance-driven pay tied directly to the value you create — structured as a percentage of internal cost savings from AI agent deployments and incremental revenue from new AI products. The more impact you drive, the more you earn. Ready to Build With Us? If you're energetic, scrappy, and ready to build something exceptional from the ground up, we would love to hear from you. Required: - Your resume. - A short note (5–10 sentences) describing the first AI agent you would build if you started tomorrow and why.

• Design, develop and maintain Generative AI applications, advanced AI models and conversational agents. • Use Gen AI techniques like Retrieval Augmented Generation (RAG), Prompt Engineering, Embeddings etc. to enhance model outcomes. • Perform evaluation on LLM output using appropriate metrics and iteratively improve results. • Stay updated with the latest industry trends and advancements in AI to implement cutting-edge solutions. • Communicate model results and solicit feedback from stakeholders at various levels.

Role Description MacPractice is looking for an Agent Builder, someone who can design, build, and ship AI agent systems that either transform how our portfolio companies operate or become standalone products their customers pay for. This is not a research role. You will be embedded directly within MacPractice, working alongside its teams to understand day-to-day operations and build AI agents that handle real work: - Customer support - Sales outreach - Onboarding - Internal documentation - Workflow automation Some of what you build will replace manual processes inside MacPractice. Some of it will evolve into new, revenue-generating capabilities delivered to MacPractice’s customer base. Either way, your work will ship to real users and have immediate, measurable impact. Qualifications - Proven track record of building products, tools, projects, startups, or side projects that went live. - Strong working knowledge of AI and machine learning tools, large language models, and agent frameworks. - Ability to go from zero to functional prototype quickly. - Comfort with ambiguity. You will often be defining the problem as much as the solution. - Bias toward action over planning. Requirements - Experience building AI agents, voice agents, or workflow automation (Nice to Have). - Background in vertical SaaS or B2B product development (Nice to Have). - Familiarity with industries like HVAC, healthcare, dental, or professional services (Nice to Have). - Previous startup or founder experience (Nice to Have). - Experience working across multiple product lines or business units (Nice to Have). Benefits - Health coverage - Dedicated building budget for APIs, tools, and infrastructure - High ownership. You define what gets built and how. - Equity and growth path tied to the impact you create. - Base Salary: Competitive. - Variable Compensation: Aggressive performance-based pay tied directly to the value you create. - Equity: Available. Details based on role scope and track. Company Description MacPractice, headquartered in Nebraska, provides specialized practice management and clinical software for healthcare providers across the United States. As part of Valsoft Corporation, MacPractice operates with a long-term ownership mindset, focused on product excellence, operational autonomy, and sustainable growth.

• Develop and maintain large-scale systems supporting critical use-cases including frontier model training for AI Infrastructure, driving reliability, operability, and scalability across global public and private clouds. • Collaborate on tooling for HPC, GPU Training, and AI Model training workflows. • Build tools and frameworks to improve observability, define actionable reliability metrics, and enable fast issue resolution, driving continuous improvement in system performance. • Establish frameworks for operational maturity, lead sustainable incident response protocols, and conduct blameless postmortems to improve team efficiency and system resilience. • Implement SRE fundamentals, including incident management, monitoring, and performance optimization, while designing automation tools to reduce manual processes and operational overhead. • Work with engineering teams to deliver innovative solutions, uphold high standards for code and infrastructure, and contribute to hiring for a diverse, high-performing team.