---
title: 'Deployment Strategist at Context'
canonical: 'https://feeny.ai/job/deployment-strategist-context-san-francisco-ss9jcxyrs2se'
type: 'job'
last_seen: '2026-09-06'
---

# Deployment Strategist at Context

- **Company:** Context
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-15
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/context/3d21cd47-c75f-4f40-abcc-d17a6094a926

## Job description

## 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

## About Context

## Company Overview
- **One-liner**: Context provides an enterprise AI execution layer platform that captures internal workflows and expert judgment to deploy agents for task completion.
- **Entity Type**: Private (Seed Stage)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Not publicly available

## Core Business
- **Primary industry**: Enterprise AI / Agentic AI Platform
- **Target customers**: Large enterprises in financial services, legal, insurance operations, consulting, telecom, and the public sector—teams whose work is high-volume, document-heavy, and judgment-dependent.
- **Mission or purpose**: "Change computing forever" — the company aims to advance the state of the art in computing and bring those advances to the broadest possible audience.

## Products & Services
- **Workspace**: A collaborative environment where human teams and AI agents complete tasks side by side using the same documents, spreadsheets, decks, and kanbans.
- **Engine**: A permissioned runtime that runs inside the customer’s perimeter (hosted, VPC, on-prem, or air-gapped), giving agents identity, tools, and compute with zero standing credentials.
- **Unify**: The institutional-context layer that accumulates knowledge across runs in a traversable filesystem, with a `.context/` directory at every level where agents write what they learn.
- **Evals**: A system that scores every agent run against rubrics authored by the customer’s own experts, turning accepted work into golden sets and corrections into measurable improvement.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**:
  - **Total Funding**: $11.0M (Seed Round, led by Lux Capital, announced May 2025)
  - **Annual Revenue**: ~$500,000 (estimated, per LinkedIn data)
- **Notable Investors/Partners**: Lux Capital (lead investor in seed round)
- **Growth Signals**:
  - Headcount: 34 employees with +3.3% monthly growth
  - 12,473 LinkedIn followers (+0.2% monthly)
  - 800+ pre-built connectors across data warehouses, documents, CRMs, ticketing, and internal systems
  - Multiple press mentions in TechCrunch, The Information, VentureBeat, and PR Newswire in 2025-2026
  - Announced GA of enterprise agent platform (May 2026)
  - Launched air-gapped AI agents for regulated industries (April 2026)

## Competitive Advantages
- **Closed-loop learning system**: Every completed task makes the next one more accurate and cheaper to serve, creating a compounding data moat.
- **Enterprise-grade security and compliance**: Agents inherit user permissions from the customer’s IdP at every action, hold zero standing credentials, and can run fully air-gapped or on-prem.
- **Model-agnostic routing**: Each step routes to the cheapest model that clears a custom rubric, allowing frontier models to handle only genuinely novel tasks while keeping costs low.
- **Plain-English runbooks**: Workflows are defined in plain English that operators, engineers, and compliance teams can all read—no prompt engineering required.
- **Data sovereignty**: Customer traces, corrections, and institutional context belong solely to the firm and never leave its control or feed other models.

## Strategic Focus
- **Deployment speed**: Most teams run their first production workflow within a few weeks—pick one process, connect the systems, have experts review early runs.
- **Vertical expansion**: Pre-built agents and use cases for semiconductors, financial services, consulting, telecom, public sector, healthcare, legal, insurance, and supply chain.
- **Self-improving systems**: Evals gate every change; accepted outputs become reusable standards and training data for custom models the customer owns and serves.
- **Flexible deployment**: Hosted, in customer VPC, on-prem, or fully air-gapped, with identity and compute staying on the customer’s side of the perimeter.

## Why Work Here
- **Culture & values**: The company emphasizes "Kick butt, have fun, don't cheat, love our customers and change computing forever." Principles and values are described as the "soul" of the company.
- **Team size**: Small (~34 employees), offering significant ownership and impact.
- **Work environment**: Collaborative—teams and agents work on the same files in the same environment.
- **Growth trajectory**: Rapidly growing startup (Seed-stage, $11M raised, GA announced in May 2026) with strong media attention and enterprise traction.
- **Engineering culture**: Focus on advancing the state of the art in AI, working with frontier models (Claude, GPT, Gemini, open weights), and building infrastructure for enterprise-grade agent deployment.
- **Remote/hybrid policy**: Not explicitly stated; headquarters in San Francisco.
- **Notable perks**: Opportunity to work on cutting-edge enterprise AI infrastructure with a small, high-impact team; direct exposure to customers and real-world deployment challenges.

## Sources
1. [context.ai](https://www.context.ai/)
2. [Context About Page](https://context.ai/about)
3. [Context Press Page](https://www.context.ai/press)
4. [Context FAQ](https://www.context.ai/faq)
5. [LinkedIn - Context](https://www.linkedin.com/company/contextworkspace)
6. [Ashby Careers Page](https://jobs.ashbyhq.com/context)

## Other roles at Context

- [Summer Intern](https://feeny.ai/job/summer-intern-context-san-francisco-4fze4c1wnzwp) — San Francisco, CA
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- [MTS](https://feeny.ai/job/mts-context-san-francisco-16e7633nekf9) — San Francisco, CA
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