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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 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.
Responsibilities
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Identify, design, and develop foundational data infrastructure components capable of handling millions or billions of events daily
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Analyze and improve the robustness and scalability of existing data processing infrastructure
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Partner with product teams to understand functional requirements and deliver solutions that meet business needs
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Write clear, well-tested, and maintainable infra-as-code and software for both new and existing systems
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Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
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Participate in an on-call rotation to address critical incidents when necessary
Requirements
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6+ years building production backend systems (distributed systems, APIs, data services).
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Strong skills in at least one backend language (e.g., Go, Python, Java, Rust) and API design (REST/gRPC).
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Demonstrated ability to own services end-to-end: design docs, implementation, testing, deployment, on-call, and iteration based on real usage.
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Strong engineering fundamentals: clean, maintainable code, thoughtful abstractions, strong design patterns, and systems that are easy to evolve.
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Solid data modeling and query skills (SQL) and experience with at least one of:
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Streaming/eventing (Kafka/Pub Sub/Kinesis, etc.)
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Workflow/compute (Airflow/Spark/Flink/Trino, etc.)
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OLTP/OLAP stores and data lakes (Postgres + warehouse/lake tech)
AI augmentation mindset:
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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.
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You have engineering judgment and you understand when AI Augmentation can fail or create team dynamics issues, putting mitigation mechanisms and guardrails in place.
Nice to have
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Experience building self-serve platforms (control planes, templates/golden paths, paved roads, multi-tenant services).
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LLM/AI product exposure: prompt/response telemetry, eval datasets, embeddings/RAG metadata, model/tool traces, privacy-safe logging.
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Security and governance experience: least-privilege access, auditability, data retention, PII handling.
About Together AI
Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as Flash Attention, Hyena, Flex Gen, and Red Pajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.
Compensation
We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $240,000 + 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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About Together AI

Together AI
Series BData annotation company.
51-200
Employees
San Francisco
Headquarters
$1.25B
Valuation
Reviews
4.0
19 reviews
Work Life Balance
3.5
Compensation
4.5
Culture
4.0
Career
4.3
Management
3.5
79%
Recommend to a Friend
Pros
Cutting-edge technology stack and interesting technical challenges
Competitive compensation packages with equity
Strong engineering culture with focus on code quality
Cons
Organizational changes and restructuring can be disruptive
Internal politics in some teams
Work-life balance can be challenging during product launches
Salary Ranges
0 data points
Mid/L4
Mid/L4 · Product Designer
0 reports
$156,800
total / year
Base
$156,800
Stock
-
Bonus
-
$133,280
$180,320
Interview Experience
3 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Coding Round
5
System Design Round
6
Onsite/Virtual Interviews
Common Questions
Coding/Algorithm
System Design
Technical Knowledge
Infrastructure/SRE
MLOps/Machine Learning
News & Buzz
Together AI – Weekly Recap - TipRanks
Source: TipRanks
News
·
6w ago
Tech firms move toward significant office leases in S.F.’s Showplace Square - San Francisco Chronicle
Source: San Francisco Chronicle
News
·
7w ago
Together AI Emphasizes Practical Framework for Selecting Open-Source Models in Production - TipRanks
Source: TipRanks
News
·
7w ago
Baseten nabs $300M from IVP, CapitalG to challenge Together AI in inference - Tech Funding News
Source: Tech Funding News
News
·
8w ago