Prompt Engineer; Conversational Design

About Us

We’re a fast-growing software startup serving the self-storage industry. Our AI-powered omni-channel agents (web, SMS, and voice) help operators automate sales and service, deliver 24/7 customer support, and create a smoother experience for tenants. Everything we build is centered around clarity, great design, and giving customers exactly what they need. As we scale, we’re looking for a Prompt Engineer who is excited to push the boundaries of conversational AI — crafting agents that reason clearly, act reliably, and deliver exceptional customer experiences across every channel. ⭐ About the Role We’re hiring a Prompt Engineer to design, build, and iterate on the next generation of our conversational agents. You’ll work closely with our Product, Engineering, and Customer teams to architect multi-agent systems that automate complex workflows across the self-storage customer journey. This is a technical and highly creative role. You should be someone who loves understanding how LLMs think, who writes clean and structured prompts, and who is constantly experimenting, testing, and evaluating agent behavior in real-world scenarios. If you’re excited about shaping the future of AI-powered automation — and you enjoy blending system design, prompt craftsmanship, and rapid iteration — this role is a great fit. ⭐ What You’ll Do Agent Development

• Design, build, and refine conversational agents that automate property management workflows
• Create prompt frameworks that balance deterministic structure with flexible natural-language interaction.
• Architect multi-step agents using OpenAI, Claude, Gemini, or similar LLM platforms.
• Implement and test strategies for conversation state, memory, grounding, and controlled behavior.
• Translate operator workflows and business logic into structured LLM decision-making.

Testing & Iteration

• Run systematic A/B tests on prompts, instructions, and agent configurations.
• Build evaluation loops to measure agent quality, accuracy, hallucination risk, and task success.
• Analyze real customer conversations to identify improvements and reduce failure cases.
• Maintain version-controlled prompt libraries and internal documentation.

RAG, NLP, and Conversation State

• Design retrieval-augmented generation (RAG) strategies using embeddings, vector databases, and structured knowledge.
• Apply NLP intent classification concepts to structure agent reasoning and fallback handling.
• Manage conversation history effectively — understanding when to summarize, truncate, or pass forward context.
• Collaborate with our Engineering team to evolve our data pipeline and system architecture.

Cross-Functional Collaboration

• Partner with Product to translate customer needs into agent capabilities.
• Work with Engineering to implement agent logic within our AI engagement platform.
• Collaborate with Customer Success to diagnose issues and improve agent reliability.
• Support Sales with demos or prototypes illustrating agent behavior.

Process, Quality, & Reliability

• Maintain robust testing environments for multi-agent workflows.
• Document prompt patterns, design principles, and system behaviors.
• Bring an analytical and disciplined mindset — ensuring every agent delivers predictable, high-quality outputs.
• Work efficiently in a fast-moving product environment where experimentation and iteration are core to the role.

⭐ What You Bring Experience & Skills

• 2–5+ years of experience working with LLMs, conversational AI, NLP systems, or related fields.
• Hands-on experience building with OpenAI, Claude, Gemini, or similar LLM APIs.
• Strong understanding of:
• Prompt engineering best practices
• Multi-agent orchestration
• NLP intent modeling
• Structured LLM approaches (tool calling, function schemas, JSON modes, validation)
• RAG architectures, chunking strategies, and retrieval evaluation
• Conversation memory, summarization, and context-handling techniques
• Ability to debug reasoning failures and systematically improve agent performance.
• Strong writing skills and an instinct for clear communication — both to humans and LLMs.
• Comfort experimenting, testing, and working through ambiguity.

Bonus

• Experience with vector databases, embeddings, or semantic search.
• Familiarity with TypeScript, Python, or similar languages used for agent orchestration.
• Background working with customer-facing AI systems or high-volume conversational apps.
• Experience in SaaS, automation platforms, or AI products.

⭐ Why This Role Matters Our AI agents are the core of our platform. Your work will directly shape how tens of thousands of tenants interact with self-storage operators — from renting a unit to getting support to managing their accounts. You’ll play a central role in pushing the boundaries of what’s possible with conversational AI in our industry, helping us build agents that are more capable, more reliable, and more human-centered every month. If you made it this far and this sounds like a great fit, have a look at our website and check out our mascot, Hoover the owl. What are his colors? Apply tot his job Apply To this Job