7-8+ years of experience in distributed systems or large-scale backend architecture.
Experience in designing and scaling search, recommendation, or ranking systems.
Led or significantly contributed to ML or LLM production integrations.
Proven technical leadership in mentoring and influencing direction.
Strong experience with data-intensive systems and event-driven architectures.
Responsibilities
Architect the core intelligence of our sourcing engine.
Define scalable frameworks for model evaluation and personalization.
Create architectural patterns for integration with existing products.
Drive technical discovery for emerging technologies.
Improve evaluation pipelines for new models and product lift.
Build systems enabling fast iteration without quality compromise.
Partner with Product and Design to establish AI-focused user experiences.
Benefits
Collaborative and innovative work environment.
Opportunities for professional development and mentorship.
Potential for impacting product direction and architecture.
Encouragement of experimentation with emerging technologies.
Full Job Description
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 Stack
The Process
Here'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
