Staff Backend Engineer

Key Responsibilities

• Build core backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration.
• Create scalable SaaS foundation including multi-tenant architecture, tenant isolation, usage tracking, quotas, audit logs, background jobs, and service boundaries.
• Power agent-facing retrieval workflows by building APIs and interfaces for AI agents, MCP tools, CLIs, and internal applications to access context, provenance, confidence signals, and warnings.
• Partner across product and infrastructure teams to balance fast experimentation with long-term reliability as the project moves from prototype to production.
• Operate services by instrumenting with metrics, logs, traces, alerts, and dashboards; use observability tools to monitor and improve reliability.
• Contribute to technical direction by shaping architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices.
• Communicate effectively in a dynamic, collaborative environment and take full ownership of developed AI solutions to ensure they are innovative, scalable, maintainable, and aligned with user workflows.

Requirements

• Strong experience building production-grade, user-facing software systems; self-starter capable of tackling complex problems with minimal supervision.
• Experience with LLMs, prompt engineering, and building applications powered by GenAI.
• Proven track record of delivering software into production that is actively used by users.
• Exposure to cloud-native environments (e.g., AWS, GCP, Azure).
• Experience using observability tools to understand and troubleshoot system behavior.
• Practical AI mindset focused on delivering high-quality, real-world solutions.
• Comfortable with quick iteration, releasing prototypes, collecting feedback, and working through ambiguity.
• Proven initiative, ownership, and ability to drive projects forward.
• Collaborative attitude with effective communication and openness to feedback.

Nice-to-Haves

• Experience building or working with agent frameworks or multi-agent workflows.
• Experience as a data analyst or with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, Databricks).
• Experience building tools for data engineering.