C

Context

Analytics dashboard for AI chatbot interactions

Forward Deployed Strategist

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 2 years of hands-on experience in investment banking, private equity, hardware engineering, management consulting, or a similar knowledge-intensive field.
  • Know the day-to-day workflows of the relevant industry, including less-visible operational pain points.
  • Demonstrate strategic thinking and the ability to scope and sequence a deployment plan.
  • Communicate effectively with senior operators and earn their trust.
  • Show high agency and comfort with ambiguity.

Responsibilities

  • Develop and own the deployment strategy for an industry vertical, identifying high-value workflows to automate and sequencing the work.
  • Work directly with Fortune 500 customers to understand their operations, map workflows, and translate findings into a deployment plan.
  • Partner with the engineering team to ensure the product and agent configurations meet industry-specific needs.
  • Build relationships with senior stakeholders at customer organizations and serve as a trusted advisor on AI adoption.
  • Feed field learnings back into the product roadmap to shape future development.

Desired Qualifications

  • Have light technical fluency, including comfort demoing products, talking to engineers, and understanding how AI systems work.
  • Have experience in a client-facing or consulting capacity.
  • Have prior exposure to AI/ML products or enterprise software deployments.

About the Company

Context

Analytics dashboard for AI chatbot interactions

Context.ai analyzed unstructured text data from user conversations with AI-powered apps to help teams understand user behavior, popular topics, debugging signals, and AI performance. Its dashboard collects and parses chat transcripts to surface insights about how users interact with agents and how well the models respond. It differentiates itself by focusing on conversational data from LLM-based experiences rather than just clicks and by applying NLP-based analysis to transcripts for product and model improvements. Its goal was to provide clear, actionable visibility into AI-assisted interactions so teams can make better product decisions and evaluate models, a path that led to its team joining OpenAI for AI model evaluation tooling after seed funding and acquisition.

Company size
1-10
Company stage
Seed
Total funding
$3.5M
Headquarters
London, United Kingdom
Founded
2023

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