Member of Technical Staff (Commercial) - Tech/Start Up track

Artificial Analysis

$130K — $160K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years in client-facing technical roles at top tech companies, preferably in AI
  • Proven experience owning client relationships and navigating complex commercial terms
  • Analytical mindset with a focus on the details behind the data
  • Genuine interest in and understanding of frontier AI developments
  • Exceptional communication skills and high responsiveness

Responsibilities

  • Partner with leading AI teams as the primary contact point
  • Develop in-depth expertise in AI and AI benchmarking
  • Field client requests and provide fast, accurate responses
  • Advise clients on interpreting benchmarking results
  • Manage the entire client relationship lifecycle including renewals and escalations
  • Ensure successful delivery of benchmarks and commitments to clients
  • Engage in product and technical tasks within the benchmarking team

Benefits

  • Work at the cutting edge of frontier AI
  • Become an expert through hands-on experience
  • Collaborate closely with top AI labs and technology companies
  • Opportunity for significant self-improvement and professional growth
  • Competitive compensation including equity
Full Job Description
Job Description - Member of Technical Staff (Commercial) - Tech

Location: San Francisco (on-site at our offices)

The Opportunity

Our benchmarks are the reference point for the companies building AI, and demand from AI labs, hardware companies and enterprises is growing exponentially. We are hiring Members of Technical Staff (Commercial) to own our client relationships end to end: become a trusted partner to frontier AI companies, act as the first point of contact for customer requests including benchmarking of pre-release models, ensure first-class delivery of our services and deepen our partnerships strategically and commercially.

This is an incredible and unique opportunity to work at the very cutting edge of frontier AI, and will require you to become a first-class expert in AI and AI benchmarking. This is a client-facing product role, not a pure go-to-market or traditional sales role. You will represent complex benchmarks that carry independent authority, which means holding your own in methodology conversations with the most sophisticated AI teams and enterprises in the world. Around 80% of your time will be client work; the remaining 20% is hands-on product and technical work inside our benchmarking team, keeping your expertise current and your credibility real. One line we never cross: commercial relationships never influence benchmark results, and this role is the guardian of that boundary in every client conversation.

What You'll Do
Partner directly with the teams building frontier AI - the labs, hardware companies and enterprises whose models, chips, inference platforms and agents define the field - as their primary relationship at Artificial Analysis
Ramp into deep expertise in AI and AI benchmarking. You will not arrive an expert, but you will become one - working shoulder to shoulder with our product and technical teams, running benchmarks, and building a view of the industry and the stack that almost no role outside a frontier lab offers
Own the front door for our clients: field inbound requests, including pre-release model benchmarking, and get them to the right answer fast
Advise and support clients to interpret their results in context: what the numbers show about their models' strengths and where they sit relative to the field
Grow the business end to end, from first outreach through to close, with senior support on commercial terms
Own your accounts through their full lifecycle - renewals, escalations, business reviews - and hold the line on everything we've committed to
Ensure delivery lands: benchmark runs, custom analysis and every commitment we make to a client
Contribute directly to product and technical work within your pillar, from evaluation reviews to analysis - roughly 20% of your time
Embrace an AI-native workflow, using cutting-edge AI tools to generate leverage in a fast-changing industry

What We're Looking For

This posting is for candidates from client-facing product and technical roles at top technology companies, not pure go-to-market profiles.

Backgrounds include: client-facing product roles, Forward Deployed Engineering, Technical Pre-Sales, Sales Engineering or Solutions Architecture at companies like Stripe, Vercel, Datadog, Databricks, Scale AI, Hugging Face, OpenAI, Anthropic, or comparable high-bar startups, with 3+ years of experience in client-facing technical roles.

You have owned client relationships around a technical product: you can hold a technical room, get into the product detail, and translate a sophisticated product into commitments customers value. You want to be closer to frontier AI than a conventional GTM role allows, with real product work as part of the job rather than a side effect.

Across all candidates, we require:
• 3+ years in a leading tech startup, with strong preference for existing AI company experience
• Proven client ownership. You have led engagements, been the person a client calls, navigated commercial terms and held relationships through difficult moments - not supported someone else who did
• Analytical, with the instinct to get into the detail rather than stay at the summary level. Our work rewards people who care about how a number was produced, not just what it says
• Genuine, demonstrable interest in frontier AI. We want people with informed opinions about where AI is heading, not just people who use AI tools
• Exceptional written and verbal communication, high responsiveness, and full ownership of your accounts

Nice to have:
• Working proficiency in Python
• Technical background - a degree in computer science, engineering, mathematics or a related field, or hands-on experience with ML systems
• Prior exposure to AI or ML, whether professionally, through research, or through serious side projects
• Experience at an early-stage company, or in a role without an established playbook
• Familiarity with the AI infrastructure landscape: inference providers, hardware, agent frameworks
• Fluency in Mandarin

Competitive compensation including equity

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