Realpage connects property management software, analytics and AI to help real estate owners and operators improve property and portfolio performance. Backed by Battery.
About the role
Technical Strategy & Architecture: Own the end-to-end architecture for AI products and platforms, including: Model selection strategy (e.g. Google vs. OpenAI, small vs. large models), multi-agent and workflow orchestration patterns (responder/thinker pattern, tool calling, agentic frameworks), and data and retrieval architecture (RAG, hybrid search, knowledge graphs, semantic caching). Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- The position requires two (2) years of experience in a senior or leadership role
- Working with coding assistants, such as Windsurf, Cursor, Codex, etc.
- Architecting and shipping complex AI systems to production at scale
- Leading multi-engineer initiatives and mentoring others
- Making data-driven tradeoffs between speed, quality, and cost
More about this role
Position Title: Lead AI Engineer
Hours: Monday – Friday, 8:00 am to 5:00 pm, 40 Hours/Week
Technical Strategy & Architecture: Own the end-to-end architecture for AI products and platforms, including: Model selection strategy (e.g. Google vs. OpenAI, small vs. large models), multi-agent and workflow orchestration patterns (responder/thinker pattern, tool calling, agentic frameworks), and data and retrieval architecture (RAG, hybrid search, knowledge graphs, semantic caching). Evaluate and introduce emerging technologies such as: next-generation LLMs and multimodal models, real-time streaming infrastructures, and advanced agent frameworks, workflow engines (e.g., Agents SDK, Google ADK, LangGraph, etc.).
Platformization & Reusable Capabilities: Design and lead the implementation of shared AI services and SDKs, including reusable RAG pipelines and ingestion frameworks, common UI components and design patterns for AI copilots and agents, and modular reusable coding practices for agentic back-end processes. Establish standards and best practices for: prompt design and versioning, model and retrieval evaluation, and observability, logging, and incident response for AI...
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