Backend Software Engineer

### Who you are
- 6+ years building production backend systems (distributed systems, APIs, data services)
- Strong skills in at least one backend language (e.g., Go, Python, Java, Rust) and API design (REST/gRPC)
- Demonstrated ability to own services end-to-end: design docs, implementation, testing, deployment, on-call, and iteration based on real usage
- Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, strong design patterns, and systems that are easy to evolve
- Solid data modeling and query skills (SQL) and experience with at least one of:
- Streaming/eventing (Kafka/PubSub/Kinesis, etc.)
- Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
- OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)
- AI augmentation mindset:
- You understand the state-of-the-art ways engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, eval-driven iteration, retrieval/knowledge grounding), and you apply this thoughtfully to your own development and to the systems you build
- You have engineering judgment and you understand when AI Augmentation can fail or create team dynamics issues, putting mitigation mechanisms and guardrails in place
- Experience building self-serve platforms (control planes, templates/golden paths, paved roads, multi-tenant services)
- LLM/AI product exposure: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging
- Security and governance experience: least-privilege access, auditability, data retention, PII handling

### What the job involves
- You’ll join the Data Platform team, responsible for building the backend services and “data products” that power how data moves through the company
- We create the core platform primitives - high-quality event streams, reliable access layers, and developer-friendly APIs/tools - so teams across the org can self-serve what they need and ship faster
- You’ll design, build, and run backend services that create value from our company data, and make our data platform more self-serve (DIY)- so product and engineering teams can easily create and operate event-driven architectures, publish/consume streams, define access models, and ship data products end-to-end
- You’ll also build LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products
- Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
- Analyze and improve the robustness and scalability of existing data processing infrastructure
- Partner with product teams to understand functional requirements and deliver solutions that meet business needs
- Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
- Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
- Participate in an on-call rotation to address critical incidents when necessary

### Benefits
- Competitive health insurance plans
- Dental and vision insurance
- Pre-tax flexible spending accounts
- Mental health support and services
- Income protection & retirement
- 401(k) plan
- AD&D insurance
- Life insurance
- STD & LTD insurance
- Monthly team lunches
- Flexible time off policy
- Team-driven celebrations and events
- Monthly commuting stipend + pre-tax bene