Who You Are- You have 7-8+ years of experience building distributed systems or large-scale backend architecture.
- You've designed and scaled search, recommendation, or ranking systems that balance precision, recall, and performance.
- You've led or heavily contributed to ML or LLM integrations in production.
- You have a track record of technical leadership: mentoring others, introducing frameworks, and influencing technical direction.
- You have strong experience with data-intensive systems, asynchronous processing, or event-driven architectures.
What You'll Do- Architect the core intelligence behind Scout.
- Own the end-to-end architecture of our sourcing engine, from data ingestion to ranking, personalization, and model orchestration.
- Define scalable frameworks for retrieval, reranking, and LLM-driven evaluation to ensure we deliver highly personalized, high-quality results.
- Create architectural patterns that integrate Scout seamlessly with our existing products to power repeatable sourcing workflows.
- Lead agentic experimentation and evaluation.
- Drive technical discovery for emerging technologies, including memory systems, schema, prompt libraries, embedding models, and agentic frameworks.
- Improve and extend our evaluation pipelines to test new models and determine lift in specific parts of our product.
- Build systems that allow fast iteration without compromising quality or reliability. Our priorities are reliability, performance, cost, and then developer productivity.
- Shape AI-native product experiences.
- Partner with Product and Design to define patterns that make LLM-powered sourcing intuitive and fast.
- Translate ambiguous product goals into scalable technical designs that unblock new workflows for our users.
- Establish best practices for building AI-first UX patterns, including agentic flows, async interactions, and structured outputs.
- Provide architectural leadership across engineering.
- Mentor and guide engineers on the team, raising the bar for system design, documentation, and technical decision making.
- Drive clarity in cross-team architecture with Flow, Data, and Infra, ensuring Sourcing evolves as a cohesive, maintainable system.
- Set long-term technical direction for how we build AI-powered sourcing systems.
Our StackThe ProcessHere's our interview process:
- Recruiter Screening: 20 mins
- Technical Screening (Debugging): 45 mins
- Technical Screening (System Design): 45 mins
- Jam Session: 2 hours
- Behavioral interviews with our Head of Engineering and CEO: 30 mins each
- References
