Forward Deployed Engineer

CData is the data layer between AI and ROI—delivering the connectivity, context, and control that make enterprise AI more accurate. One platform for live access and data replication across 350+ sources, semantic intelligence that ensures context-aware responses, and built-in governance for every AI-to-data interaction. Powering AI and analytics workloads for Anthropic, Databricks, Microsoft, Google, Palantir, and more than 10,000 customers worldwide. Behind that impact is a global team of passionate problem-solvers, engineers, and innovators who are redefining what’s possible in data connectivity. Headquartered in Chapel Hill, North Carolina, CData has over 500 team members, with offices in North America, Europe, and Asia. We take pride not just in what we build, but in how we build it: together, with curiosity, creativity, and a shared drive to push boundaries.

About the role

The Forward Deployed Engineer is the hands-on delivery force on CData’s most strategic enterprise engagements. You’ll embed with customer teams to deploy CData Connect AI, configure MCP servers, build agent integrations, write production code that connects customer systems to AI, and validate end-to-end functionality. This builder role operates on a multi-sprint cadence, with field insights directly shaping the Connect AI roadmap.

Responsibilities

• Embed and deliver in customer environments
  • Deploy Connect AI, configure MCP servers, connect data sources, and validate agent workflows in production.
  • Build and test AI agent integrations using Connect AI Workspaces and Toolkits with correctly scoped data access.
  • Configure semantic context and governance layers for accurate, permission-aware agent responses across connected sources.
• Build and ship AI integrations
  • Write production code in Python, Java, or C# connecting customer systems to Connect AI via MCP, REST, OData, and CData drivers.
  • Implement integration patterns and security configurations defined with the engagement architect.
  • Contribute to and reuse the FDE team's reference architectures, blueprints, and sample agents.
• Operate and iterate in production
  • Deliver iterative solutions on a multi-sprint cadence with weekly customer demos, validation checkpoints, and AI workflow refinement.
  • Own deployment health, monitor MCP performance, troubleshoot agent accuracy, and ensure a smooth Customer Success handoff.
  • Triage and resolve production issues with escalation to the architect or product team as needed.
• Close the product feedback loop
  • Document product gaps and agent behavior patterns from the field; feed prioritized insights to the Connect AI product team.
  • Capture reusable patterns, code snippets, deployment recipes, and troubleshooting notes to compound across the FDE team.

Requirements

• 4–7 years in software engineering, data engineering, or technical consulting with hands-on delivery experience.
• Track record of shipping production code in customer-facing or customer-impacting roles.
• Experience explaining technical concepts to non-technical stakeholders and leading discussions.
• AI-literate — understands how LLMs consume data, what MCP does, and how agents use tools and context to reason over enterprise sources.
• Proficient in Python, Java, or C# with experience building API integrations, data pipelines, or connector-based workflows.
• Comfortable with data plumbing: SQL, REST APIs, ODBC/JDBC, JSON/XML parsing, and multi-source data mapping.
• Able to configure governed access for AI agents — RBAC, OAuth 2.1, and semantic scoping.
• Builder mentality — ships working solutions in ambiguous customer environments within tight iteration cycles.
• Strong communicator who can explain technical AI concepts to non-technical customer stakeholders clearly and confidently.
• High agency; comfortable as the primary engineering presence on a customer engagement.

Nice to have

• Hands-on experience with the MCP protocol and AI agent frameworks (LangChain, CrewAI, Copilot Studio).
• Prior FDE, professional services, or solutions-engineering experience at a data, analytics, or AI platform company.
• Exposure to modern data stacks (Snowflake, Databricks, Salesforce) and cloud-native deployment patterns.

Location: Remote, U.S. (EST or West Coast preferred). Travel: Up to 25%. Applicants must be currently authorized to work in the United States on a full-time basis; CData is unable to provide visa sponsorship.

Pay

The typical base pay range for this role across the U.S. is $150,000–$175,000 per year. In Eastern Time and West Coast markets, the expected base pay range is $150,000–$175,000, depending on experience and qualifications.

Benefits

• Medical, Dental, and Vision plans with company-paid insurance premiums.
• Health Savings Account with company contribution.
• Flexible Savings Account and Dependent Care FSA.
• 20-day PTO and 11 paid holidays.
• 401k with 100% company match up to 6% of contribution.
• Remote-friendly, high-trust culture that empowers collaboration, celebrates curiosity, and encourages innovation.
• Professional development and learning opportunities tailored to career goals.