Founding Software Engineer

Job description

**Location:** San Francisco, CA (Hybrid or Remote-First) **Type:** Full-Time, Founding Team Member **Compensation:** Competitive salary + founding-level equity ### **About Us** We are an early-stage AI startup building the first AI-native productivity assistant that seamlessly integrates into your digital life to handle email, calendars, contacts, and tasks and make sure you never drop the ball. Backed by leading venture capital firms including Village Global, Neo, SV Angel, and researchers and executives from Anthropic, Microsoft, Cognition, Quora, Atlassian, and Waymo, we’re assembling a world-class founding team passionate about building scalable, human-aligned AI systems that transform how life gets done. ### Our founding team includes repeat entrepreneurs, AI researchers, and early engineers from companies such as Meta, Palantir, Dropbox, and Databricks. Collectively, we’ve built products used by millions, led teams at unicorn-stage AI companies, raised over $100 million in venture capital, and achieved exits to Fortune 500 firms. Together, we bring deep expertise across AI systems design, large-scale engineering, and growth at the intersection of technology and human productivity. ### **The Role** As a **Founding Software Engineer**, you’ll report directly to our CTO and own the design and implementation elements of our core agentic infrastructure — from system architecture and data pipelines to the reasoning and orchestration layers that make our agents intelligent and reliable. You’ll work closely with the founders to define the product roadmap, scale our AI systems, and shape the company’s engineering culture from the ground up. This is a hands-on, high-impact role for a builder who thrives in early-stage environments and wants to have a lasting influence on the trajectory of a company and its technology. ### **What You’ll Do** - Design, build, and scale core backend systems for an autonomous AI assistant platform. - Architect agentic systems capable of real-time reasoning, tool-use, and long-term memory. - Develop agent orchestration frameworks integrating LLMs, APIs, and user-facing logic. - Collaborate with founders on technical vision, product direction, and infrastructure decisions. - Contribute to early customer pilots and feedback loops to refine the AI product. - Establish best practices for code quality, reliability, and scalable experimentation. - Help grow and mentor a small, high-performing technical team as the company scales. ### **Who You Are** - 5+ years of software engineering experience, ideally in systems-level or backend development. - Strong **systems design** thinking — you approach problems architecturally, not just tactically. - Experienced **agent builder** — you’ve built or contributed to agentic frameworks, multi-step reasoning systems, or autonomous tools. - Proficient in Python, TypeScript, or Go (experience with LangChain, LlamaIndex, or similar frameworks a plus). - Understanding of LLM APIs, embeddings, vector databases, and retrieval-augmented generation (RAG). - Excited by early-stage ambiguity and the opportunity to build foundational technology from scratch. - Entrepreneurial mindset — comfortable wearing multiple hats and moving quickly in a startup environment. ### **Nice to Have** - Prior experience as a **founding engineer** or early startup team member. - Experience integrating AI with real-world tools or enterprise systems. - Track record of building and deploying production-grade AI or ML systems. - Contributions to open-source AI frameworks or developer tools. - Interest in human-AI collaboration, reasoning architectures, and long-horizon autonomy. ### **Why Join Us** - Founding-level impact and equity. - Direct influence over product and technical direction. - Work with a tight-knit team pushing the boundaries of agentic AI. - Backed by top-tier early-stage investors who believe in the vision. - Opportunity to help define the culture, values, and engineering DNA of a company from day one. - Building a product from pre-launch with no legacy code and lots of autonomy