5+ years of experience in software engineering, machine learning, and applied AI with a track record of driving projects to completion
Strong software engineering fundamentals (testing, modular design, dependency injection) in Python
A track record of taking AI and LLM-powered features from initial concept through deployment and long-term production maintenance
Experience implementing automated testing strategies for non-deterministic systems, and strong debugging and analytical skills for ambiguous model behavior
A strong understanding of prompt engineering and prompt lifecycle management, RAG architectures and retrieval evaluation, and LLM limitations and failure patterns
Solid experience in using Data Analytics techniques (SQL, analysis and visualizations) to inform Product decisions and delivery
A heavy product mindset to deeply understand our product and our customer needs to design the right solutions for them
Strong tech leadership and mentorship skills, and the ability to independently drive projects to completion
Clear communication of trade-offs, risks, and system performance to stakeholders
Proven experience driving ambiguous projects to completion, mentoring teams, and communicating complex technical risks to stakeholders
The ability to design robust, production-grade evaluation at scale using advanced metrics and statistical validation
Deep expertise in model fine-tuning, adversarial red-teaming, and safety testing to protect the system from edge-case vulnerabilities