✨ We are looking for an experienced Senior Applied AI Engineer to join a US-based B2B SaaS project and take ownership of building and delivering AI-powered features.
This role is ideal for an engineer who has hands-on experience bringing AI solutions into production, working with LLMs, forecasting models, and scalable backend systems.
You’ll have the opportunity to drive AI architecture, shape technical decisions, and build features that deliver real business value to customers. About the Project Our client develops a B2B SaaS platform serving the dumpster rental industry in the US.
The platform currently supports approximately 650 business customers, helping them manage orders, assets, clients, and operational data. The next stage of product development focuses on integrating AI-powered capabilities that help businesses analyze their data, forecast demand, and make better operational decisions. For example, AI will help customers understand whether they should invest in additional rental assets or outsource upcoming orders based on demand forecasts.The product runs on AWS, with a strong focus on data security and customer data isolation. Responsibilities: * Design, develop, and deploy production-ready AI features using LLMs and forecasting models. * Build AI-powered solutions that allow customers to explore business data and receive actionable insights through natural language. * Develop demand forecasting models and recommendation systems to support business decisions. * Design and maintain AI architecture within a multi-tenant SaaS environment. * Ensure strict data isolation and security across customer accounts. * Optimize AI solutions for response quality, performance, latency, and operational costs. * Take end-to-end ownership of AI feature development, from technical design to production delivery. * Contribute to the AI product roadmap and future feature development.
Requirements: * Strong hands-on experience in Python backend development. * Practical experience integrating LLM APIs (OpenAI, Anthropic, or similar) into production applications. * Experience implementing RAG pipelines and/or text-to-SQL solutions. * Proven experience with demand forecasting or time-series modeling in real-world business applications. * Strong knowledge of SQL and data modeling. * Hands-on experience with AWS cloud services. * Experience working with multi-tenant SaaS architectures, including customer data isolation. * Proven track record of delivering at least one AI-powered feature to real end users. * Ability to independently own technical decisions and deliver solutions end-to-end. * Availability to maintain working-hour overlap with US business hours.
Nice to Have: * Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar LLM orchestration frameworks. * Hands-on experience with Amazon Bedrock. * Knowledge of data privacy regulations such as CCPA/CPRA or GDPR. * Experience working with SOC 2 or similar security standards. * Previous experience in logistics, rental services, field services, or marketplace products. * Experience developing recommendation systems or customer segmentation solutions.
What Makes This Opportunity Interesting: * Work on a real B2B SaaS product with an established customer base. * Build customer-facing AI features with direct business impact. * Take ownership of AI architecture and technical implementation. * Work on a combination of LLM-powered functionality, demand forecasting, and intelligent recommendations. * Contribute to a growing AI roadmap with opportunities to influence future product development. * Fully remote, full-time engagement with a US-based project.
What We Offer: * Competitive salary in USD * Paid vacation and sick leaves. * Medical insurance and well-being support. * PE accounting and support for smooth collaboration. * A supportive team that values fresh ideas and professional growth.
We’d love to hear about the AI features you’ve built and launched into production, especially projects involving LLM integration, demand forecasting, or business intelligence.
