Role Overview
As a Founding AI Engineer, you’ll be more than a developer, you’ll be a co-creator of the company’s DNA. You’ll take end-to-end ownership of our AI infrastructure and product experience: architecting systems, integrating LLMs, and shaping how humans and intelligent agents collaborate.
You’ll thrive in ambiguity, move fast, and balance technical depth with product clarity. This is a rare opportunity to build from scratch and see your work directly influence product, culture, and company trajectory.
Key Responsibilities
- Design, develop, and deploy AI-powered full-stack features using Python (backend, AI orchestration) and React/TypeScript (frontend).
- Build, fine-tune, and integrate large language models (LLMs) via APIs (OpenAI, Anthropic, or LangChain-style frameworks).
- Own the full ML lifecycle, from data collection and preprocessing to model training, evaluation, deployment, and monitoring.
- Develop API-first architectures (REST/GraphQL) that enable seamless integration and scalability.
- Build and maintain secure, privacy-by-design data models using PostgreSQL and cloud-native infrastructure (AWS, GCP, or Azure).
- Implement robust DevOps practices with Docker, GitHub Actions, and CI/CD pipelines.
- Collaborate directly with founders to define the technical roadmap, product strategy, and engineering culture.
- Balance speed and rigor, shipping quickly while building foundations for long-term scale.
Required Skills & Qualifications
- Minimum of 3 years of relevant experience as a Software Engineer or Machine Learning Engineer.
- Strong full-stack experience in Python (backend + ML) and React/TypeScript (frontend).
- Proven experience building and deploying ML models in production environments.
- Deep understanding of machine learning concepts, algorithms, and frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Experience integrating LLMs and designing AI agent systems or orchestration layers.
- Strong understanding of data modeling, security, and privacy principles.
- Skilled in DevOps tools and modern CI/CD workflows (Docker, GitHub Actions, etc.).
- Entrepreneurial mindset, thrives in chaos, works autonomously, and delivers outcomes.
Nice-to-Have Qualifications
- Prior experience in an early-stage startup or founding-engineer capacity.
- Contributions to open-source AI/ML projects.
- Experience with MLOps tools (MLflow, Kubeflow) or container orchestration (Kubernetes).
- Interest in product design, UX, and building tools founders love.
Who You Are
- You move fast, learn faster, and own outcomes.
- You care deeply about clarity, speed, and user experience.
- You’re comfortable wearing multiple hats, from data pipelines to design polish.
- You want to build the next wave of AI-native products, not just use them.