01Overview
The Role
Were hiring a lead backend engineer to own and harden the systems at the center of our product. Youll work in a Python backend with clear service boundaries, ship production changes with high ownership, and raise the bar on reliability, performance, and design.
This is not a CRUD API role. Youll reason about ranking and retrieval quality, multi-tenant data models, external API complexity, and LLM systems that have to work under real support-desk constraints.
What You'll Work On
- Search & retrieval: Contemporary search and retrieval systems (e.g., Elasticsearch, PgVector), airflow, filters, embeddings, and result quality
- Answer / QA services: orchestration around LLMs, prompt engineering, and agentic tool use
- Integrations & auth: connectors and OAuth/SSO/SAML flows across various support platforms
- Async & data pipelines: Async job systems, data pipelines, and ingestion workflows for heterogeneous source data
- APIs & data model: REST services, ORM/data modeling, and database migrations, multi-tenant correctness
- Production systems: Redis, container orchestration (e.g., Kubernetes), observability, feature flags, and robust testing frameworks
What We're Looking For
- 7+ years building production backend systems (or equivalent depth)
- Expert-level Python and comfort in large existing codebases
- Strong experience with relational data modeling (Postgres), migrations, and query performance
- Experience with search or information retrieval (Elasticsearch/OpenSearch, vector search, or similar): or clear evidence you can ramp fast
- Experience designing reliable integrations with third-party APIs (auth, rate limits, webhooks, eventual consistency)
- Familiarity with async job systems (Celery, Sidekiq, RQ, or similar) and production debugging
- High bar for code quality: tests, clear interfaces, careful rollouts, written design when the problem warrants it
- Ability to own problems end-to-end with minimal hand-holding
Must Have
- LLM/RAG systems in producti .
