Software Engineer - MTS

Context•San Francisco, CA

65d

About The Position

At Context AI, Software Engineers (MTS) build the platform that powers AI agents executing complex, high-stakes work for Fortune 100 enterprises. You'll work at the intersection of frontier language models and production-grade software engineering, creating systems that enable AI to perform production-quality work knowledge workers do every day—not just chat or simple automation. As an MTS Engineer, you'll architect and build the core product that grounds AI in institutional intelligence—the tribal knowledge, business rules, workflows, and quality standards that define how organizations actually operate. Whether it's building rich editors where AI generates client deliverables, orchestrating agent workflows that analyze million-line codebases, or designing graph-powered context surfaces that feed gigabytes of data to AI systems, you'll use your engineering expertise and product creativity to build software that delivers 30-40% productivity improvements and 90%+ cycle time reductions for our customers. You'll have direct impact on how enterprises deploy AI across telecommunications, finance, consulting, biotech, and technology. Your code will power AI agents that operate 24/7/365 as continuously improving teammates, executing engineering diagnostics, financial analysis, client deliverable generation, and code shipping with six-figure analyst quality. As an MTS Engineer, you'll experience the autonomy of a startup with the resources, mentorship, and stability of a well-funded AI company. You'll work in small, agile teams and own end-to-end execution of core platform features

Requirements

Relevant experience in software engineering building production web applications
Strong engineering background, preferred in fields such as Computer Science, Software Engineering, Mathematics, Physics, or related technical disciplines
Strong full-stack coding skills with proficiency in TypeScript/JavaScript and React; Python experience or willingness to learn
Experience building production systems—APIs, data pipelines, web applications, real-time UX, or complex frontend architectures
Track record of shipping features that users love—demonstrated attention to UX, performance, and polish
Intellectual curiosity about AI/ML systems and their application to real-world problems

Nice To Haves

Experience building collaborative editors (CRDT, OT, multiplayer systems)
Strong visual design sensibility or prior work with design systems and component libraries
Publications or medals (IOI/ICPC, NeurIPS, SOSP) showing technical depth
Familiarity with LLM fine-tuning, retrieval, or agentic chains
Experience with cloud infrastructure (AWS, GCP, Azure) and modern DevOps practices
Prior work in high-growth startups or platform/infrastructure teams

Responsibilities

Architecting and building end-to-end product features that feel magical yet familiar—rich editors, interactive dashboards, multi-modal canvases where AI executes complex work
Designing Autopilot UX—orchestrating agent plans and live previews so users can see AI think, execute, and iterate in real time with sub-100ms interactions
Building the integrations layer—seamless connections to Google Workspace, Microsoft 365, Notion, Slack, Linear, and 300+ other tools that ground AI in institutional intelligence
Engineering the design system & component library—performant, accessible React/Tailwind components that scale from mobile to 4k monitors
Building the learning flywheel infrastructure—systems that capture subject matter expert feedback and continuously improve AI agent capabilities
Collaborating on architecture decisions with Product, Design, and Engineering teams to turn customer insights into cross-customer platform capabilities
Owning full-stack features from database schema to API design to pixel-perfect frontend, ensuring production quality at every layer

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume