Forward Deployed Engineer - MTS

About ContextWere on a mission to unlock the next frontier of productivity for knowledge workers.Context AI is building the future of enterprise AI-systems that dont just answer questions or automate simple tasks, but execute the complex, judgment-heavy work that drives real business outcomes. The constraint blocking AI from creating true enterprise value isnt model intelligence anymore; its institutional intelligence: understanding how your organization operates, where information lives, what quality standards matter, and how work actually gets done.Our platform solves this by automatically learning each organizations unique context-the tribal knowledge, business rules, internal lexicon, and tacit expertise that defines production-quality work. Each Context task can connect to gigabytes of data across entire codebases, data rooms, and operational systems, enabling AI agents to perform real work that knowledge workers do: engineers analyzing firmware logs to identify root causes, bankers running due diligence on multi-terabyte data rooms, analysts refreshing deliverables with live market data, and consulting teams creating client presentations and websites.Weve proven our system with Fortune 100 customers, achieving 30-40% productivity improvements, reducing cycle times by over 90%, and deploying solutions in days rather than months. Context AI operates 24/7/365 across global teams, freeing knowledge workers to focus on strategic initiatives and new growth frontiers.Why ContextMassive Impact: The potential of enterprise AI is unbounded, and were 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 moreReal Technical Challenges: Design systems no one else has ever built in order to tackle problems that no one else has ever solvedOwnership 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 ownershipElite Technical Team: Weve assembled a superstar team hailing from Apple AI, Microsoft Research, Google, Stripe, Ramp, and more. Work with and learn from the bestWhat Youll DoAt Context AI, the Forward Deployed Software Engineer (FDSE) role is where cutting-edge AI meets real-world complexity. Youll 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, youll 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 its "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?", youll use your engineering expertise, creativity, and problem-solving skills to build AI agents that deliver 30-40% productivity improvements and 90%+ cycle time reductions.Youll have the rare opportunity to gain deep insight into and directly influence some of the worlds most critical industries-telecommunications, finance, consulting, biotech, technology. By building on Contexts AI platform and grounding it in customer data, youll help organizations unlock AI that executes real work, operating 24/7/365 as a continuously improving teammate.As an FDSE, youll 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. Youll work in small, agile teams and own end-to-end execution of high-stakes deployments, including:Collaborating with engineers on architecture and design decisions for AI agents that execute complex workflowsWrangling massive-scale data-integrating codebases, operational systems, data rooms, and proprietary datasets into stable pipelines that ground AI in institutional intelligenceBuilding custom AI workflows tailored to customer needs: engineering diagnostics, financial analysis, client deliverable generation, code shippingDeveloping integrations that connect Context agents to customer tools and systems-Slack, Linear, Google Workspace, proprietary platformsEngineering the learning flywheel-building systems that capture subject matter expert feedback and continuously improve AI agent capabilitiesEngaging directly with customer stakeholders, from engineers and analysts to executives, understanding their workflows and demonstrating AI impactShaping team strategy and driving projects from ideation to deployment, increasing your pain threshold to deliver real value and measurable productivity gainsEmbedding product insights from customer deployments into Contexts core platform, turning customer-specific solutions into cross-customer capabilitiesWhat We ValueAgency: Innovation happens when team members think from first principles and go above and beyond to achieve objectives-not by simply completing tasksStrong Engineering Fundamentals: A highly analytical approach and eagerness to solve technical problems with data structures, distributed systems, cloud infrastructure, APIs, and modern frameworksObsession with Execution Quality: Understanding the difference between AI that assists and AI that executes production-quality work-and building systems that achieve the latterComfort with Ambiguity: Experience or curiosity about working with massive-scale, unstructured data to solve valuable business problems where "how we do things" isnt documentedProduct Creativity: Our engineers dont just turn inputs into outputs. We expect team members to think creatively and invent ways to improve the productLow Ego: We understand that the outcome matters more than who gets the credit. Team members share wins and dont play politicsAdaptive 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 constantlyWhat We Require2+ years of relevant, post-college work experience in software engineering, preferably in customer-facing or deployment rolesStrong engineering background, preferred in fields such as Computer Science, Software Engineering, Mathematics, Physics, or related technical disciplinesStrong coding skills with proficiency in programming languages such as Python, TypeScript/JavaScript, Java, or similarExperience building production systems-APIs, data pipelines, web applications, or integrations with enterprise softwareIntellectual curiosity about AI/ML systems and their application to real-world problemsAbility 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)Nice to HaveExperience with AI/ML systems, LLMs, or agent frameworksPrior work in consulting, professional services, or customer-facing technical rolesFamiliarity with enterprise software ecosystems (Google Workspace, Slack, Linear, etc.)Background in or curiosity about specific domains: telecommunications, finance, consulting, biotech, engineering systemsExperience with cloud infrastructure (AWS, GCP, Azure) and modern DevOps practicesTrack record of driving measurable impact in customer deployments or product implementations