Backend Software Engineer — Data Platform & AI Data Products
Indexed description
Responsibilities
- Contribute to backend services that enhance the data platform’s capabilities (APIs, control planes, automation, governance).
- Help enable DIY workflows for teams across the company:
- Define/publish events and schemas
- Create/consume streams and subscriptions
- Establish access models (authz, row/field-level controls where applicable)
- Manage dataset/catalog metadata, lineage, versioning, and retention
- Contribute to end-to-end data products: ingestion → validation/quality → enrichment → serving (APIs/streams) → observability → adoption.
- Work on prompt categorization and enrichment services: taxonomy design, labeling workflows, classifier/rules integration, evaluation, drift/quality monitoring, and safe rollouts.
- Learn to own reliability: SLOs, alerting, performance/cost tuning, incident response, and postmortems.
- Partner cross-functionally with ML/LLM, infra, security, and product teams to define crisp contracts and deliver durable platform primitives.
- 0–4 years building production or project-based backend systems (internships, coursework, and personal projects count).
- Solid fundamentals in at least one backend language (e.g., Go, Python, Java, Rust) and some exposure to API design (REST).
- Eagerness to own work end-to-end: design docs, implementation, testing, deployment, and iteration based on real usage.
- Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, and a desire to build systems that are easy to evolve.
- Basic data modeling and SQL skills, and some familiarity 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 curiosity:
- You’re curious about how engineers use AI/LLMs to build software faster and better (e.g., coding copilots, agentic workflows, retrieval/knowledge grounding), and you’re eager to apply this to your own work.
- You understand that AI tools can fail or create issues, and you’re thoughtful about when and how to apply them.
- Any exposure to self-serve platforms, developer tooling, or multi-tenant services.
- Coursework or projects involving LLM/AI products: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
- Passion for good quality code, highly readable, SOLID principles, design patterns, Domain Driven Design.
- Awareness of security and governance basics: least-privilege access, auditability, data retention, PII handling.
Compensation
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $120,000 - $170,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal Opportunity
Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy
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