Data Engineer | Together AI Global Negotiation Guide

Negotiation DNA: Pre-IPO Equity + Base + Bonus | AI Inference & Optimization | 400% YoY Growth | $3.3B Valuation | +20% Kernel Innovation Premium

Region	Base Salary	Equity (Options/RSU est.)	Bonus	Total Comp
San Francisco	$148K–$198K	$38K–$62K	10–15%	$178K–$248K
Seattle	$141K–$188K	$36K–$59K	10–15%	$169K–$236K
Remote US	$133K–$178K	$34K–$55K	10–15%	$160K–$223K

Negotiation DNA

Data Engineers at Together AI build the data pipelines, storage systems, and analytics infrastructure that power Together Kernel's inference optimization decisions and Together AI's business intelligence. You engineer the data layer that captures inference telemetry from millions of API calls, model performance metrics across GPU architectures, and customer usage patterns that drive Together AI's 400% YoY revenue growth. Your pipelines feed the analytics that determine kernel optimization priorities, pricing strategy, and capacity planning for a platform built on FlashAttention's breakthroughs. (Source: Together AI data infrastructure requirements; engineering job listings, 2025.)

Level Mapping: Together AI Data Engineer ≈ Google Data Engineer L4–L5 · Meta Data Engineer IC4 · Amazon DE III · Databricks Data Engineer · Snowflake Data Engineer · Anthropic Data Engineer

Together Kernel — The FlashAttention Premium

Together AI created FlashAttention — the single most impactful algorithmic optimization in modern AI, used by every major AI lab. Together Kernel is the proprietary inference optimization framework that delivers state-of-the-art speed and efficiency. With 400% YoY revenue growth and a $3.3B valuation, Together AI needs data engineers who can build pipelines that process GPU telemetry, inference latency data, and kernel performance metrics at massive scale. As a Data Engineer, you build the data infrastructure that measures and optimizes the layer that makes AI inference fast and cheap everywhere — the foundational infrastructure of AI deployment. This justifies a 20–25% Kernel Innovation premium. Your frame: "I build the optimization layer that makes AI inference fast and cheap everywhere — and my data pipelines are how Together AI knows what to optimize next."

Global Levers

1. Telemetry at Scale: "I build the data infrastructure that captures inference performance across millions of API calls. My pipelines directly inform kernel optimization decisions that drive revenue growth."
2. Pre-IPO Data Infrastructure Equity: "Data infrastructure is a compounding asset — every pipeline I build serves the company for years. My equity should reflect the long-term value of the data layer I'm constructing."
3. AI-Native Data Engineering: "Data engineering for an inference platform requires handling GPU telemetry, kernel profiling data, and real-time latency metrics — this is significantly more specialized than standard data engineering."
4. Growth-Stage Data Demands: "At 400% YoY growth, data volume is exploding. I'll be building pipelines that need to handle 10x scale increases within a year — that's a unique and demanding challenge."

Negotiate Up Strategy: "I'm excited to build Together AI's data infrastructure at this critical growth inflection. My competing offer is $240K TC from [Databricks/Snowflake/Google]. I'm asking for a base of $195K, equity valued at $60K/year at current 409A, and a 15% bonus target — approximately $245K TC. My accept-at floor is $222K TC. Below that, the risk premium for pre-IPO equity doesn't justify leaving a liquid package. I'd also want a $18K sign-on bonus and clarity on my scope — specifically whether I'll own the core inference telemetry pipeline or the business analytics data layer."

Evidence & Sources

• Together AI $3.3B valuation and data infrastructure scaling needs (TechCrunch, 2025)
• FlashAttention telemetry and kernel profiling data requirements (Together AI engineering blog, 2025)
• Levels.fyi Data Engineer compensation at AI infrastructure companies (2025–2026)
• Glassdoor data engineering salary data for growth-stage AI startups (2025–2026)