As a Full Stack Lead at our rapidly growing, well-funded pre-seed startup in the PropTech industry, you will drive new feature initiatives from concept to version 1. Our platform, used by hundreds of addicted and dependent users, highlights the value we deliver. You'll leverage your understanding of user needs and technology to create solutions that enhance our mission to revolutionize the real estate industry. With years of runway and a growing customer base, this is an excellent opportunity to join a dynamic and innovative team.
Mission:
Backed by experienced industry executives, we are building an AI-driven platform to transform the home-buying experience. By leveraging data, we empower top real estate professionals to exceed customer expectations. Our flexible work environment involves in-office collaboration to find product-market fit, with plans for a balanced mix of on-site and remote work as we grow. We are committed to rapid testing, learning, and iterating to consistently deliver value to our users.
Responsibilities:
As a Full Stack Lead, you'll own entire feature areas from start to finish, beginning with understanding product design and crafting scalable solutions. You'll focus on real-world demand for your features, ensuring they support our entire user base. Key responsibilities include:
Leading the end-to-end development of new features, from ideation to version 1.
Proactively reaching out to users to gather feedback and leveraging metrics to make product adjustments in real time.
Collaborating with cross-functional teams to design, implement, and launch new features.
Developing secure and reliable data pipelines and processing frameworks to support real estate agents with both client and third-party data.
Performing prompt engineering to extract structured data and insights from existing data and generate hyper-personalized content for real estate agents.
Building systems like latency-sensitive telephonic systems for natural conversations, accessing external data that lack APIs using web data extraction methods, event processing for live data enrichment, and leveraging the latest LLM techniques for consistent, reliable offerings at scale.
Focusing on traditional AI areas like lead scoring, creating models to help agents prioritize outreach and automate processes.
Our Culture:
We emphasize in-person collaboration, ensuring quick pivots and real-time teamwork. Every team member fully owns their features, from concept to deployment, supporting them post-launch and designing success metrics. We foster a supportive environment where everyone helps each other succeed. Success is measured through direct user feedback, prioritizing features based on user willingness to pay, and tracking adoption and usage.
Must-Have Skills:
5+ years of experience in programming languages such as Python, Java, or TypeScript.
Experience in data engineering, including the creation of secure and reliable data pipelines.
Expertise in system architecture and API design for seamless integration.
Proven experience in designing and implementing scalable backend systems.
Proficient in SQL for data manipulation and insights extraction.
Ability to move quickly and take ownership of projects.
Strong focus on measuring the success of features and using metrics to guide decisions.
Experience in testing ideas in ways that don't scale to gather valuable customer insights.
Located in Seattle (in-person collaboration is key during the early stages).
Nice-to-Have:
Experience in PropTech or real estate technology.
Previous startup experience.
Familiarity with frontend technologies (React, CSS, JavaScript).
Experience with AI or machine learning.
Experience with LLMs and prompt engineering.
Knowledge of tools such as Pandas, Flink, Kafka, Spark.
Compensation:
Competitive startup salary.
Generous equity stake.
Health insurance.
Flexible Time Off policy.
Commuting benefits.
Office snacks and weekly catered lunch.
Dog-friendly office (bring your own dog or enjoy petting others).
Conveniently located in Pioneer Square, near both the light rail and the Sounder train.