Software Engineer - MTS

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, including:

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

Frontend : TypeScript · React · Next.js · Tailwind CSS

Backend : Python (FastAPI) · Postgres · Redis · custom graph store

AI/ML : OpenAI / Anthropic APIs + in-house fine-tunes

Infrastructure : Kubernetes · GCP

Agency: Innovation happens when team members think from first principles and go above and beyond to achieve objectives—not by simply completing tasks

Strong Engineering Fundamentals: A highly analytical approach and eagerness to solve technical problems with data structures, distributed systems, cloud infrastructure, APIs, and modern frameworks

Obsession with Execution Quality: Understanding the difference between AI that assists and AI that executes production-quality work—and building systems that achieve the latter

Comfort with Ambiguity: Experience or curiosity about working with massive-scale, unstructured data to solve valuable business problems where "how we do things" isn't documented

Product Creativity: Our engineers don't just turn inputs into outputs. We expect team members to think creatively and invent ways to improve the product

Low Ego: We understand that the outcome matters more than who gets the credit. Team members share wins and don't play politics

Adaptive and Introspective: We operate in a fast-moving environment and accordingly iterate rapidly; team members must be able to learn from their mistakes and improve constantly

You've shipped polished, user-loved web apps at scale —front-end to back-end and everything between

You sweat the details : motion, pixel-perfect layouts, sub-100ms interactions, joyful empty states

You prototype quickly , validate with users, and iterate based on data and intuition

You write clear RFCs , welcome feedback, and enjoy pair-designing as much as pair-programming

Fluent in TypeScript/React ; comfortable jumping into Python services when needed (or eager to learn)

You see AI as a design material and are excited to invent new UX paradigms around it

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

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