---
title: 'MTS at Context'
canonical: 'https://feeny.ai/job/mts-context-san-francisco-16e7633nekf9'
type: 'job'
last_seen: '2026-09-06'
---

# MTS at Context

- **Company:** Context
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-10-28
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/context/9922393f-4970-4fb9-815f-c03e9a316fd5

## 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 Member of Technical Staff, you’ll be part of the team responsible for the Context platform. You will think end to end about what it means to build the most potent enterprise AI agents and design the best interface to deploy them, and you will have broad autonomy to work wherever you believe the highest leverage is across the entire stack. Our MTS work variously on underlying infrastructure, core features, agent configurations, and user experience. Additionally, you may work closely with our enterprise customers in a forward deployed role. You will own entire features, your code will ship to real customers fast, and your product and technical decisions will shape the course of the company.

## WHAT YOU’LL DO

- Own and ship features end to end across our full-stack TypeScript/React application, from design through implementation to production
- Make high-judgment calls about what to build next based on customer needs, technical debt, and product opportunity
- Work directly with Fortune 100 customers to understand their workflows and translate that into product
- Contribute across the stack (frontend, backend, infrastructure, agent systems) wherever you see the most leverage
- Shape engineering culture and practices at an early-stage company where your decisions have outsized impact

## WHAT WE’RE LOOKING FOR

- Strong full-stack engineering skills with production experience in TypeScript and React
- Track record of shipping product. We care about what you’ve built, not how many years you’ve been building
- Product intuition: you can talk to a customer, identify the real problem, and figure out what to build
- High agency. You don’t wait to be told what to work on
- Comfort with ambiguity and moving fast in a small team

## NICE TO HAVE

- Experience with AI/ML systems, LLM integrations, or agent frameworks
- Background working with enterprise customers or in forward-deployed engineering roles

## WHY CONTEXT

- Massive Impact: The potential of enterprise AI is unbounded, and we're at the frontier. At Context, you will build software that transforms the nature of work for thousands of engineers, bankers, analysts, consultants, product managers, lawyers, and more
- Real Technical Challenges: Design systems no one else has ever built in order to tackle problems that no one else has ever solved
- Ownership That Matters: We trust our team members to direct influence on product direction and own entire systems. At Context, you propose, build, and ship features with full autonomy and ownership
- Elite Technical Team: We've assembled a superstar team hailing from Apple AI, Microsoft Research, Google, Stripe, Ramp, and more. Work with and learn from the best

## 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
- [Forward Deployed Engineer - MTS](https://feeny.ai/job/forward-deployed-engineer-mts-context-san-francisco-g9798haj5h5m) — San Francisco, CA
- [Deployment Strategist](https://feeny.ai/job/deployment-strategist-context-san-francisco-ss9jcxyrs2se) — San Francisco, CA
- [MTS](https://feeny.ai/job/mts-attention-engineering-palo-alto-ms5nedt51mcb) — Palo Alto, CA