Forward Deployed Engineer - MTS

San Francisco Officefull-timemid
OtherForward Deployed Engineer
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Quick Summary

Overview

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,

Technical Tools
OtherForward Deployed Engineer

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.

Responsibilities

~2 min read

At Context AI, the Forward Deployed Software Engineer (FDSE) role is where cutting-edge AI meets real-world complexity. You'll embed directly with Fortune 100 customers to build AI agents that execute complex, high-stakes work—not just chat or simple automation. As an FDSE, you'll be at the intersection of frontier language models and institutional intelligence, building systems that perform production-quality work knowledge workers do every day.

FDSEs work side by side with our customers, rapidly understanding their most complex workflows and architecting solutions that ground AI in institutional intelligence—the tribal knowledge, business rules, and quality standards that define how organizations actually operate. Whether it's "How do we enable AI to diagnose firmware failures across million-line codebases?" or "How can AI run due diligence on multi-terabyte M&A data rooms with six-figure analyst quality?", you'll use your engineering expertise, creativity, and problem-solving skills to build AI agents that deliver 30-40% productivity improvements and 90%+ cycle time reductions.

You'll have the rare opportunity to gain deep insight into and directly influence some of the world's most critical industries—telecommunications, finance, consulting, biotech, technology. By building on Context's AI platform and grounding it in customer data, you'll help organizations unlock AI that executes real work, operating 24/7/365 as a continuously improving teammate.

As an FDSE, you'll experience the autonomy of a startup with the resources, mentorship, and stability of a well-funded AI company. Your contributions will have direct impact on how enterprises deploy AI and the productivity of knowledge workers. You'll work in small, agile teams and own end-to-end execution of high-stakes deployments, including:

Nice to Have

~1 min read
  • Experience building production systems—APIs, data pipelines, web applications, or integrations with enterprise software

  • Intellectual curiosity about AI/ML systems and their application to real-world problems

  • Ability and interest to travel up to 25-50% as needed to customer sites for onboarding, training, and deployment (flexible based on customer needs and personal preferences)

    • Experience with AI/ML systems, LLMs, or agent frameworks

    • Prior work in consulting, professional services, or customer-facing technical roles

    • Familiarity with enterprise software ecosystems (Google Workspace, Slack, Linear, etc.)

    • Background in or curiosity about specific domains: telecommunications, finance, consulting, biotech, engineering systems

    • Experience with cloud infrastructure (AWS, GCP, Azure) and modern DevOps practices

    • Track record of driving measurable impact in customer deployments or product implementations

    Location & Eligibility

    Where is the job
    San Francisco Office
    On-site at the office
    Who can apply
    Same as job location

    Listing Details

    Posted
    April 15, 2026
    First seen
    July 14, 2026
    Last seen
    July 14, 2026

    Posting Health

    Days active
    0
    Repost count
    0
    Trust Level
    19%
    Scored at
    July 14, 2026

    Signal breakdown

    freshnesssource trustcontent trustemployer trust
    Employees
    30
    Founded
    2006
    View company profile

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    context learning finland oyForward Deployed Engineer - MTS