Senior AI Engineer, Roofstock

• 5+ years of experience in AI engineering, with at least 2 years building or deploying Generative AI systems and intelligent agents in real-world environments. Experience with traditional ML concepts and pipelines is a plus
• Experience building LLM-powered applications in real-world business contexts, such as AI copilots, agent workflows, or task automation systems
• Hands-on experience with LLMs, agent frameworks (e.g. LangChain, LangGraph, or CrewAI), and RAG architectures
• Deep proficiency in Python and strong fluency with Git, including CI workflows and collaborative development practices
• Experience deploying and operating systems in AWS, including tools like Lambda, S3, EC2/ECS/EKS, and IAM
• Familiarity with observability and monitoring tools such as Datadog, Kibana, or CloudWatch
• Strong understanding of AI software engineering best practices and core ML fundamentals, including testing, versioning, and deployment strategies
• Experience working independently in distributed teams, with effective asynchronous communication skills across time zones
• Strong written and verbal communication skills in English, including the ability to participate in live discussions and document decisions clearly
• A growth mindset, high ownership, and a team-first attitude

Desirable

• We’re looking for a Senior AI Engineer who thrives at the intersection of Generative AI, intelligent agents, and systems engineering
• You’ll help architect and deliver GenAI solutions that augment operations, automate decision-making, and enhance the experience for operators, investors, and residents
• You’ll take an active role in shaping and delivering technical solutions, applying deep expertise in AI/ML, strong software engineering practices, and a collaborative mindset
• You’ll play a key role in shaping our agentic infrastructure and partnering with teams across the organization to bring AI-powered capabilities to life
• Drive the design and implementation of scalable AI systems, with a focus on Generative AI, including LLMs, agentic workflows, and RAG pipelines, as well as applying machine learning where appropriate
• Work cross-functionally with product, design, and operations teams to identify high-impact problems and develop AI-driven solutions
• Lead initiatives to bring models from prototype to production, including evaluation, observability, and post-deployment monitoring
• Contribute to the design of our agentic infrastructure, enabling tool use, task routing, and human-in-the-loop workflows
• Collaborate with product, platform, and data teams to AI-enable internal services and tooling, design model interfaces, integrate data sources, and develop reusable orchestration patterns to support contextual, domain-specific intelligence
• Own the reliability, performance, and operational health of services in production, including CI/CD workflows, infrastructure-as-code, and real-time monitoring
• Mentor and support engineers, fostering a culture of technical excellence, collaboration, and continuous learning
• Leverage your software engineering background to write clean, maintainable Python code, guide architectural decisions, and advocate for best practices in a fast-moving environment
• Stay current on GenAI and ML trends, and evaluate emerging tools and techniques for practical integration