Backend Software Engineer — Data Platform & AI Data Products

Togetherai; San Francisco (CA); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Competitive compensation

Startup equity

Health insurance

Other competitive benefits

Job summary

Togetherai in San Francisco is looking for a Backend Developer to join our Data Platform team. In this role, you will enhance backend services and create data products that empower teams across the organization. Ideal candidates should have strong fundamentals in backend languages and eagerness to own projects from design to deployment.

The position offers a competitive salary range of $120,000 - $170,000 plus equity and benefits, fostering a collaborative environment where AI tools are explored for improving workflow.

Qualifications

• 0–4 years of experience in backend systems including personal projects.
• Strong engineering fundamentals and maintainable code practices.
• Curiosity about AI tools and their application.

Responsibilities

• Contribute to backend services for data platform enhancements.
• Enable DIY workflows for teams across the company.
• Own reliability aspects including SLOs and alerting.

Skills

Backend language fundamentals (Go, Python, Java, Rust)

API design (REST)

Basic data modeling and SQL skills

Streaming/eventing knowledge

Eagerness to own projects end-to-end

Tools

Kafka/PubSub/Kinesis

Airflow/Spark/Flink/Trino

Postgres

Job description

About the Role

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 contribute to backend services that create value from our company data, and help make our data platform more self-serve 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 work on LLM-adjacent services such as prompt categorization/taxonomy, enrichment, and metadata systems that turn raw telemetry into trusted, usable products — with mentorship and support from experienced engineers.

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.

Requirements

• 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.

Nice to have

• 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.

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