Role Description We are rebuilding what an agency account team looks like. The old model takes six people and three months to plan, write, design, build, and ship a client website. We are replacing that with one AI-native marketer using AI to ship the same work in days. You will be the first hire in this new role, owning the delivery and results for a portfolio of accounts and the qualified leads and booked jobs those clients pay us for. What You'll Do - Own account outcomes. The qualified leads and booked jobs for your accounts are yours, and so is the channel mix. - Build and ship websites and marketing collateral end-to-end with AI. - Drive organic, content, and SEO performance. - Partner with the paid team on paid performance. - Automate the repetitive tasks. - Aim every build at marketing results. - Equip the Senior Client Success Manager with what they need. Qualifications - 4+ years in performance marketing, lead generation, or growth marketing, ideally at a digital agency. - Demonstrated experience shipping production work with AI tools such as Claude, Claude Design, Vercel, n8n, or AI agents. - Balance of marketing judgment and technical orchestration skill, with a slight technical lean. - Lead-generation marketing experience in service-based industries. - A portfolio with real shipped work – websites, landing pages, automations, or agent systems. - Authorization to work in the United States. Requirements - Direct experience marketing for home services businesses (contractors, restoration, HVAC, plumbing, roofing, etc.). - Record of replacing legacy WordPress or multi-person agency workflows with AI-native builds. - Comfort with modern deployment stacks (Vercel, Netlify, or similar). - Working knowledge of analytics and lead tracking platforms (GA4, WhatConverts, CallRail, or similar). Benefits - Base salary: $95,000–$110,000 - Performance bonus tied to account outcomes, paid quarterly. - Annual compensation review with merit increase eligibility. - Medical, dental, and vision coverage. - 401(k) retirement plan. - Paid time off and company holidays. - Fully remote work with equipment provided. - Access to the AI tooling stack you need to do the job, including Claude. Interview Process - Application review — we respond within 2 business days. - Asynchronous video interview — a short set of recorded questions on your own time. - Phone screen — a brief call covering your background, the role, and logistics. - Final interview with our CEO and COO — 45-minute conversation on your background, portfolio, and fit. - Paid skills project — a short, paid project that mirrors real work, with a brief walkthrough of how you approached it. How to Apply Please send us: - Your resume - A portfolio link or attached samples. Best case: a website where you did the content, design, and development using AI tools. - A short note – a few sentences is fine – on how you use AI in your marketing work today and why this role fits. We look forward to seeing what you have built.

Role Description As a Senior Engineer on the ML/AI platform team, you will play a key role in building the internal platform which supports training and deploying AI models across the entire organization. You’ll take ownership of defining the platform to enable AI model fine-tuning and batch inference by building the SDKs and supporting the infra to support these unique workloads. We are looking for someone with high ownership and the ability to be a leader in the space. - Excited to build platform-level tools, SDKs - Ability to manage cross-cutting stakeholder relationships, prioritizing customer needs first - Eager to navigate ambiguous, hairy, and technical problem spaces - Eager to jump into domains, languages, and problem areas that might be new and unfamiliar Qualifications - Bachelor’s degree in Computer Science, a related field, or equivalent practical experience - 3 years of experience with software development in one or more programming languages - 2 years of experience in designing, analyzing, and troubleshooting large-scale distributed systems - 1 year of experience leading projects and providing technical leadership - Strong proficiency in maintaining high standards for production services - Rapid coding skills and management of production services - Experience with high scale throughput and distributed systems problems Requirements - Strong communication skills and ability to contextualize problems across various audiences - Skilled at navigating ambiguity and involving the right stakeholders to address issues efficiently - Experience building and shipping products to users - Expertise in building platforms and high scale infrastructure - Visionary thinker capable of generating transformative ideas - Prior experience working with AI Platforms like Ray is a plus Benefits - Highly market-competitive compensation and benefits - Remote work flexibility - New hire equity grant and annual refresh grants

• Design, develop, and deploy scalable AI-powered applications and services. • Translate ambiguous business problems into robust technical solutions. • Build and maintain backend systems, APIs, integrations, and AI workflows. • Collaborate across frontend, backend, cloud, and AI initiatives to deliver end-to-end solutions. • Rapidly prototype and iterate on AI-driven products and internal accelerators. • Contribute to architecture decisions, engineering standards, and reusable system patterns. • Mentor junior engineers and support technical growth across the team. • Drive improvements in scalability, reliability, performance, and developer experience. • Work closely with stakeholders to balance business needs, technical trade-offs, and delivery timelines. • Continuously evaluate and adopt emerging AI tools, frameworks, and engineering practices.

• Architect AI Agents that use Tools and Skills including instantiation of MCP clients and servers. • Architect scalable end-to-end Retrieval-Augmented Generation (RAG) pipelines including data ingestion, document processing, and promoting generation. • Increase model serving layers and high-throughput data processing pipelines, employing advanced libraries to ensure ultra-low latency and efficient resource use. • Design and implement secure system architectures for all new AI products ensuring compliance with data governance and security policies. • Understand how to use Terraform for provisioning and manage Azure infrastructure-as-code. • Support automated and reproducible Continuous Integration/Continuous Deployment (CI/CD) pipelines.