Backend Software Engineer, Together AI

• 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

Desirable

• 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