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Context

Deployment Strategist

Reposted 24 Days Ago
In-Office
San Francisco, CA, USA
180K-350K Annually
Junior
In-Office
San Francisco, CA, USA
180K-350K Annually
Junior
As a Deployment Strategist, you will develop and execute deployment strategies for AI in various industries, working closely with Fortune 500 clients to map workflows and ensure product fit.
The summary above was generated by AI
About the Company

Context is the AI platform to redefine knowledge work. We:

  • Build agents that continuously learn to capture companies’ proprietary intelligence, including procedures, data, and objectives

  • Provide the work surface for them to perform complex, long-horizon tasks alongside humans in a native office suite

  • Deploy them in secure environments to Fortune 500 companies

We are a fast-moving team of engineers and researchers from Apple, Ramp, Stripe, Meta, BAIR, and SAIL. We’ve built applications with 1M+ users, launched campaigns reaching 180M+ people, and forward deployed products in some of the world’s largest teams. We’re fortunate to be backed by Lux Capital, Qualcomm Ventures, General Catalyst, and BoxGroup.

Most companies must choose between iterating on product fast and working with the biggest enterprises on earth. We have the rare privilege of doing both. Features we ship this week are in the hands of teams at Fortune 100 companies next week, meaning every product bet we make gets immediate, high-stakes signal from some of the most consequential corporate teams in the world.

Role Summary

As a Deployment Strategist at Context, you’ll be the bridge between our platform and the industries we serve. You bring deep domain expertise in your field (investment banking, private equity, hardware engineering, consulting, or similar) and a conviction that AI can transform how work gets done in that field. You’ll develop the strategy for how Context deploys into companies in your industry and then own the execution of that strategy, working closely with customers and our engineering team to deliver real outcomes.

Compensation: $180k-$350k base + competitive equity + commission. Negotiable

Interview process: initial behavioral screening, take-home case study (regarding AI deployment strategy), and two day work trial. Work trial timing is highly flexible.

Work location/schedule: this role will likely require significant travel. We can accommodate home base in San Francisco or New York City

What You’ll Do
  • Develop and own the deployment strategy for your industry vertical, identifying the highest-value workflows to automate and the right sequence to go after them

  • Work directly with Fortune 500 customers to understand their operations, map their workflows, and translate that into a deployment plan

  • Partner with our engineering team to ensure the product and agent configurations meet the specific needs of your industry

  • Build relationships with senior stakeholders at customer organizations and serve as a trusted advisor on AI adoption

  • Feed learnings from the field back into our product roadmap to shape what we build next

What We’re Looking For
  • 2+ years of hands-on experience in investment banking, private equity, hardware engineering, management consulting, or a similar knowledge-intensive field

  • You know the day-to-day workflows of your industry inside and out, including the pain points that nobody outside the industry sees

  • Strong strategic thinking and the ability to scope and sequence a deployment plan

  • Excellent communication skills. You’re comfortable in a room with senior operators and can earn their trust quickly

  • High agency and comfort with ambiguity. This role doesn’t have a playbook yet; you’ll be writing it

Nice to Have
  • Light technical fluency (comfortable demoing product, talking to engineers, understanding how AI systems work)

  • Experience in a client-facing or consulting capacity

  • Prior exposure to AI/ML products or enterprise software deployments

HQ

Context Palo Alto, California, USA Office

Palo Alto, California, United States, 94306

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