The Role
We're looking for a Senior Fullstack Software Engineer who builds with ownership, ships with discipline, and operates with integrity. You'll be a core contributor on a small, high-output team building an AI-powered platform that processes massive national datasets and delivers real-time insights to real estate professionals.
You will own features end-to-end-from UI to API to production-and be accountable for what you ship. You'll make consequential technical decisions daily, including how and when to leverage agentic AI to solve real problems. At an early-stage company, there is no hiding behind process or titles. The work is visible, the stakes are real, and the pace is relentless.
Tech Stack
- Frontend: js (React, TypeScript)
- Backend: .NET, Python, or equivalent
- Database: PostgreSQL
- Infrastructure: Cloud-native, CI/CD, observability tooling, AWS
- AI/Agentic: LLM integration, agentic workflows, tool-use patterns
What You'll Do
- Design, build, and ship fullstack features from concept through production.
- Build and maintain agentic AI systems-autonomous workflows, tool-calling agents, multi-step reasoning pipelines, and human-in-the-loop patterns.
- Own the reliability, performance, and security of what you deploy.
- Review code with rigor-challenge weak design, unclear logic, and unnecessary complexity.
- Make sound tradeoff decisions across cost, scope, quality, and timeline.
- Communicate clearly-surface risks early, document decisions, share context broadly.
- Participate in on-call rotations and respond to incidents by fixing root causes, not just symptoms.
- Mentor other engineers as the team grows, contributing to a culture of directness, accountability, and shared ownership.
Required Skills & Experience
- 5+ years of professional software engineering experience building production software across frontend and backend.
- Strong proficiency in Next.js, React, and TypeScript, with at least one backend stack (.NET, Python, or similar).
- Hands-on experience with agentic AI-you've built systems where LLMs act autonomously: tool use, multi-agent orchestration, retrieval-augmented generation, or similar patterns-not just API wrappers around chat completions.
- Solid understanding of prompt engineering, context management, guardrails, and failure modes in AI-driven systems.
- Experience with PostgreSQL or comparable relational databases at scale.
- Solid understanding of CI/CD pipelines, automated testing, and cloud-native infrastructure on AWS.
- Experience working in early-stage or high-growth environments where scope is fluid and resources are lean.
Nice to Have
- Experience with geospatial data, map SDKs (Mapbox, Google Maps), or data-heavy web applications.
- Familiarity with real estate data-tax records, parcel data, mortgage filings, or comparable sales.
- Experience with vector databases, embedding pipelines, or semantic search.
- Contributions to open-source projects or technical writing.
Who You Are
- High autonomy, high accountability. You act without waiting for permission, but every decision you make you're prepared to stand behind.
- Production-minded. You monitor what you ship, you care about observability, and you take ownership when things break.
- Pragmatic about AI. You know when an agent adds real value and when a simple rule does the job better. You don't chase hype.
- Direct and low-ego. You give and receive feedback openly. You admit when you're wrong and change course quickly. You care more about the right answer than being right.
- Self-directed. You don't wait to be told what to do. You see problems, propose solutions, and execute. You surface risks and blockers early-no surprises.
- Team-first. You credit others fairly, you help strong people get stronger, and you optimize for company impact and user trust over personal comfort.
Why PropertyPilot
- Massive market, real problem. The U.S. real estate data ecosystem is fragmented and outdated. We're building the infrastructure layer to fix it.
- Early-stage impact. Your work will directly shape the product, the architecture, and the engineering culture.
- Strong foundation. Experienced SaaS founder, proven team, and a clear product vision-not a science experiment.
- Competitive compensation and benefits.
