We are an AI-native enterprise platform automating data-heavy workflows for the private equity and growth equity industries. The company is seeking a Technical Co-Founder / CTO to join the team, owning and driving the commercial product build. This role is ideal for someone entrepreneurial, hands-on, and excited to help shape the company from the ground up. You'll be able to own the technology roadmap and architecture, with the opportunity for founder-level equity.
The business has early customer traction across several committed design customer funds and has raised early equity capital.
What you'll do:
- Own the Product Build: lead architecture, development, deployment, and scaling of the commercial platform
- Full-Stack Development: build out existing front-end and back-end systems, integrating AI/ML components and ensuring scalability and performance
- Technical Leadership: set and maintain development and documentation standards, implement commercialization best practices, and influence key product decisions
- Product Collaboration: work closely with the founding team to translate customer requirements and pain points into technical solutions
- Platform Operations: oversee infrastructure, DevOps, security, and data management to ensure reliability and compliance
- Team Building: manage and structure a team of engineers as the company grows
Who you are:
- Minimum 2+ years of hands-on software development experience, ideally in a production environment
- Proficiency in at least one modern programming language such as Python, JavaScript/TypeScript, Go, Java, etc. with demonstrated ability to write clean, maintainable, and efficient code
- Solid understanding of machine learning concepts, including experience with model training, fine-tuning, and optimization techniques (e.g., LoRA, QLoRA, parameter-efficient fine-tuning, prompt engineering)
- Experience working with popular ML frameworks such as PyTorch, TensorFlow, or JAX
- Familiarity with end-to-end ML development pipelines, including:
- Data ingestion & preprocessing: Pandas, NumPy, Apache Arrow, Hugging Face Datasets, or similar
- Model training & tuning: Hugging Face Transformers, DeepSpeed, Accelerate, PEFT libraries, or similar
- Experiment tracking: MLflow, Weights & Biases, ClearML, or similar
- Deployment & serving: FastAPI, Flask, TorchServe, BentoML, or similar
- Experience integrating vector databases (Pinecone, Weaviate, Milvus, FAISS, etc.) for retrieval-augmented generation (RAG) and semantic search
- Ability to work collaboratively in an agile development environment, communicate effectively with cross-functional teams, and deliver high-quality results under tight timelines
Compensation: base salary + bonus + equity
