Context
Forward Deployed Engineer - MTS
About this role
Context AI seeks a Forward Deployed Engineer to embed with Fortune 100 customers and build production-grade AI agents that execute complex, high-stakes workflows. You'll architect solutions grounding cutting-edge language models in institutional intelligence, delivering measurable productivity improvements across critical industries.
What you'll do
- Collaborate with customers to understand complex workflows and architect AI agent solutions
- Integrate and wrangle large-scale data from codebases, operational systems, and proprietary datasets
- Build custom AI workflows for specialized use cases like engineering diagnostics and financial analysis
- Develop integrations connecting AI agents to customer tools and systems
- Engineer feedback loops that enable continuous improvement of AI capabilities
- Engage with customer stakeholders to demonstrate impact and gather requirements
What they're looking for
- Software engineering fundamentals and system design
- Data integration and pipeline development
- API development and third-party integrations
- Cloud infrastructure and distributed systems
- Problem-solving with ambiguous requirements
- AI/machine learning application architecture
- Technical communication with diverse stakeholders
- Startup-level execution and autonomy
Benefits
- Work directly with Fortune 100 companies on high-impact AI deployments
- Influence cutting-edge AI and enterprise technology strategy
- Access to well-funded resources, mentorship, and stability
- San Francisco office location
- Ownership of end-to-end high-stakes projects
- Exposure to critical industries including finance, telecom, biotech, and consulting
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Context
Context AI builds production-grade AI agents that execute complex, high-stakes workflows for enterprise customers by grounding language models in institutional intelligence. The company is hiring Forward Deployed Engineers to embed with Fortune 100 clients and architect AI solutions that deliver measurable productivity improvements across critical industries.
View all jobs at ContextLikely interview questions
- Tell us about a time you embedded with a customer or external team to understand their complex workflows. How did you translate those insights into a technical solution?
- Describe your experience integrating multiple data sources or systems into a single pipeline. What were the biggest challenges with data quality and scale?