• Deploy and configure agentic AI workflows and AI-powered automations within client ServiceNow environments. • Translate customer business requirements into technical architectures and implementation plans. • Implement and integrate NewRocket Agent Packs and AI solutions into enterprise environments. • Work directly with customers to tailor AI solutions to their operational workflows and business processes. • Build demos, prototypes, and proof-of-concept implementations to validate AI-driven workflows with clients. • Rapidly iterate solutions with customers to refine AI-powered use cases. • Support implementation of AI orchestration, LLM integrations, and agentic decision models. • Develop integrations between ServiceNow, enterprise systems, APIs, and AI services. • Build supporting components such as scripts, microservices, automation logic, and integration services. • Implement integrations with AI platforms, APIs, and enterprise data sources. • Actively contribute to the development and evolution of NewRocket’s AI intellectual property and platforms. • Participate in workshops, discovery sessions, and technical working sessions with customers. • Diagnose and resolve technical issues across AI workflows, integrations, and automation pipelines. • Ensure deployed AI solutions are secure, scalable, and production-ready. • Contribute to internal playbooks, reusable deployment patterns, and product evolution.

About the RoleWe're hiring a Senior AI Engineer to join the team here in Boston. This is an opportunity to have a significant impact on the product. Come help us scale to the next level! You will have the opportunity to make a huge impact on a small yet growing team and culture. In this role, you will work directly on a cross-functional engineering team, reporting to the VP of Engineering. ⚡ What you'll do - Build AI Agent and Chat Capabilities – Develop AI-powered assistants using cutting-edge technologies and tooling that help our customers run their small businesses - Deploy & Scale AI Features – Build infrastructure and pipelines to support real-time AI interactions in a production environment - Experiment & Iterate – Prototype new AI applications, evaluate their performance, and continuously refine them based on user feedback - Partner with engineering and product leaders – Contribute strategically and play a key role in the product development process 🎯 What we're looking for - 5+ years of experience in AI, ML, or NLP-related engineering roles - Proficiency in Python, with preferred experience in Django, React, and PostgreSQL - Real-world experience with Retrieval Augmented Generation (RAG) and similar practices, including vector embeddings and vector databases - Hands-on experience with OpenAI and Anthropic APIs - Familiarity with LLMs and NLP techniques, including prompt engineering, fine-tuning, and evaluation - Experience with coded agentic frameworks such as Pydantic AI, LangChain/LangGraph, or similar - Experience with end-to-end MLOps practices: monitoring, deployment, and evaluation - Experience deploying AI-powered applications in production environments (e.g., cloud-based APIs, real-time processing) - Experience working on an empowered team with Product and Design as equal counterparts - Experience in an Agile Scrum environment What you bring - Sharp problem-solving instincts, especially in fast-moving, ambiguous situations - Confidence to make decisions with best-available rather than perfect information - A drive to understand why your systems behave the way they do, not just that they work, but how - Excellent written and verbal communication skills - A team-first mentality and a love of learning - Low ego, high energy 🙌 What we offer - Full Medical, Dental, and Vision Health Coverage - Computer and workspace enhancements - 401(k) plan (non-matching) - Unlimited vacation, 9 company holidays including election day, and 1 personal volunteer day a year - Company-paid Wellhub membership for fitness and wellness - Dinner covered with Uber Eats + a stocked kitchen to keep you fuele - Opportunity to take on significant responsibility and ownership in scaling a product that can change the lives of home service pros 🏠 About Topline Pro We're building an AI-powered Shopify for service businesses. We help service pros (e.g., roofers, landscapers, painters, cleaners) acquire direct business, fast. Up and running within minutes using Gen AI, our digital storefront products help pros get discovered, trusted, and booked repeatedly. Topline Pro was co-founded by Nick Ornitz (CEO) and Shannon Kay (COO), with an excellent team of 120+ rockstars and plans to expand further in 2026. We serve thousands of local service businesses and were named one of the top 50 Tech Companies building for SMBs in 2023 and 2024. We're YC-backed and well-funded, with several years of runway, and we've experienced rapid growth over the past year. We're in a phenomenal position to scale, with the financial foundation, product-market fit, and momentum to go big. You'll be joining at an inflection point, where the groundwork is laid, and the path to massive impact is clear. We believe "great candidates" do not come about simply from a check mark next to past experience. We believe in hiring people, not just skills. Even if you do not check every box but find excitement at the prospect of working with us in this capacity, please apply. Topline Pro is committed to building an inclusive workplace and assembling a team from diverse backgrounds. We ensure that individuals with disabilities receive reasonable accommodation throughout the application and interview process. We strongly encourage applications from underrepresented candidates and those from nontraditional backgrounds.

• Operate the SDLC natively with AI • Maintain quality control and operate securely in production • Structure specifications that feed the AI • Interact with diverse tools and environments

• Turn model capabilities into real product behavior. • Own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. • Debug issues across the full stack (model, orchestration, infra, UX) • Optimize for latency, cost, and production reliability • Work closely with product and engineering to translate ambiguous problems into working systems