• Build the core backend services: Design, implement, test, and operate first services for context ingestion and storage • Create a scalable SaaS foundation: Define and build architecture for a multi-tenant service • Power agent-facing retrieval workflows: Build APIs and service interfaces for AI agents • Work across product and infrastructure: Make tradeoffs between fast experimentation and long-term reliability • Operate what you build: Instrument services with metrics and improve reliability • Contribute to technical direction: Shape architecture and engineering practices for a new product area • Effective communication: Work in a highly dynamic and collaborative environment • Ownership and impact: Take full ownership of AI solutions ensuring they are scalable and aligned with real user workflows.

• Build the core backend services: Design, implement, test, and operate the first services. • Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service. • Power agent-facing retrieval workflows: Build APIs and service interfaces for retrieval. • Work across product and infrastructure: Make practical tradeoffs between fast experimentation and long-term reliability. • Operate what you build: Instrument services with metrics, logs, traces, and alerts. • Contribute to technical direction: Help shape architecture and engineering practices. • Effective communication: Contribute across teams in a highly dynamic environment. • Ownership and impact: Take full ownership of the AI solutions you develop.

• Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. • Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. • Power agent-facing retrieval workflows: Build APIs and service interfaces allowing AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. • Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. • Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. • Contribute to technical direction: Help shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. • Effective communication: Work in a highly dynamic and collaborative environment, communicate effectively, and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are innovative, scalable, maintainable, and aligned with real user workflows.

• Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. • Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. • Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. • Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. • Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. • Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. • Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.