What Makes SalesNow Different
Data scale: 8B data points, 14M records, 2.3M daily updates (vs. 1M-100M rows at typical companies)
Data ownership: You build and own Japan's largest corporate intelligence platform (vs. processing someone else's data)
AI integration: 20+ AI pipelines in production, MCP Server live (vs. "We're planning to use AI someday")
Dev tools: Claude Code MAX ($200/month), Cursor, CodeRabbit - all company-paid (vs. standard IDE, maybe Copilot)
Your code's impact: Feeds AI products used by enterprise clients, millisecond latency matters (vs. dashboards no one reads)
Career trajectory: Build Japan's data infrastructure → architect AI data products → global leverage (vs. same stack forever)
Remote work: 100% remote, no relocation required (vs. hybrid / office-required)
Why This Role Exists
AI models are commodities now. The cost of running GPT-3.5-equivalent models dropped 280x in two years. Every company has access to the same foundation models. The war moved to data - who owns it, who structures it, who feeds it to AI.
Oracle's Larry Ellison said it plainly on his December 2025 earnings call: "AI models are trained on the same public data, so they're rapidly commoditizing. AI inference on private data will be an even bigger, more valuable business." McKinsey echoes: "By 2030, the AI leaders will be defined not by who trained the biggest model, but by who built the most reliable systems on proprietary data."
SalesNow owns 14 million company records and 8 billion data points - the largest structured corporate intelligence platform in Japan. This data updates 2.3 million records daily, with differential refresh as fast as every 60 seconds. Hiring signals, funding rounds, organizational changes, press releases, job postings - all structured, all real-time, all proprietary.
This data doesn't exist inside any LLM's training set. The only way to access it is through SalesNow. That's the moat.
We need data engineers who can build and scale the pipelines that make this moat wider every day.
What You'll Build
This is not "maintain existing ETL jobs." You're building the data nervous system of Japan's corporate intelligence.
The Scale
14 million+ company records across Japan's entire business landscape - from Toyota to a 3-person startup in Okinawa
8 billion data points structured and queryable at millisecond speed
2.3 million records updated daily - hiring signals, funding rounds, organizational changes, press releases, job postings
Sub-minute differential refresh - when a company posts a new job or announces funding, SalesNow knows within 60 seconds
42+ data sources feeding into a unified schema
5 delivery formats: Web app UI / CRM integration (Salesforce, HubSpot) / MCP Server / Data API / Custom AI Agents
AI-Native Development Culture
SalesNow doesn't just "use AI." AI is the operating system of how we build software. What this means for you, concretely:
Claude Code MAX - Company-paid for every engineer. This is a $200/month tool that most individual
developers can't justify. You get it Day 1, fully covered
Monthly AI tool budget - Tens of thousands of yen per person, on top of Claude Code MAX, for any AI tool you want to try
CodeRabbit - Automated PR reviews powered by AI. Every pull request gets AI review before human review
Vibe coding culture - Not just engineers. The CEO, COO, and business teams all write code with AI assistance. When you propose a technical solution, leadership actually understands it
20+ AI pipelines in production - X post generation, candidate screening, PR monitoring, behavioral analytics, financial page generation - all running daily in production. This isn't a demo. It's how the company operates
No "AI committee" or "innovation lab" gatekeeping - You want to try a new approach? Ship it. The decision loop is measured in hours, not quarters
Why this matters for your career: In 3 years, every engineering role will require AI-native development skills. At SalesNow, you build those skills now - not by watching tutorials, but by shipping production AI systems daily.