Founding Software Engineer

Dokai is an AI sales prospect prioritization for B2B sales teams. We help sales teams identify which companies and contacts to reach out to each day. Dokai learns each customer’s ideal buyer profiles and how they currently conduct prospecting. We leverage LLM-based AI agents (including coding AI agent) to automate this workflow.

Company Culture

We take pride in the values and principles that guide our daily operations. Our core values are Integrity, Clarity, and Excellence, and they drive everything we do.

Role Description

This is a full-time, on-site role for a Founding Software Engineer based in San Francisco. The Founding Software Engineer will lead, design, develop, and maintain scalable software systems, with a focus on AI and backend web development. We are looking for someone who is excited about training our own LLM models, learns quickly, and takes strong ownership of their work.

You will work closely with the co-founders to define the engineering roadmap, architect the system, scale the team, and engage with customers during onboarding. You will also collaborate closely with the GTM team.

Qualifications

• Strong problem-solving and critical-thinking skills
• Experience deploying software applications into production
• Solid foundation in Computer Science concepts, including algorithms, data structures, system design, CI/CD, and version control
• Proficiency in backend web development, including experience with server-side frameworks
• Knowledge of Object-Oriented Programming (OOP) principles and implementation
• Expertise in Python and TypeScript
• Experience with long-running job frameworks (e.g Temporal, Airflow)
• Understanding of LLM concepts (prompt engineering, vector databases, RAG)

Preferred Qualifications

• Excited working at at high pressure startup environment
• Experience with cloud platforms (AWS, GCP, etc.) and API integrations
• Experience with production-level AI systems (training layer, inference layer, feature store, fine-tuning)
• Experience working with ranking systems
• Experience training or fine-tuning small language models