Forward Deployed Engineer

Forward Deployed Engineer

Job Summary

CData is the data layer behind enterprise AI in production. As organizations move from experimentation to mission-critical agentic workflows, they need a partner who can connect AI to live, governed data across hundreds of systems and engineers who can ship that connection inside the customer's environment.

We're hiring Forward Deployed Engineers to be the hands-on delivery force on our most strategic enterprise engagements. You'll embed with customer teams to deploy CData Connect AI, our managed MCP platform, and the broader CData stack, configuring MCP servers, building agent integrations, writing the production code that connects customer systems to AI, and validating that it works end-to-end. You'll work alongside an FDE Architect on engagement design and report into the Director of Forward Deployed Engineering.

This is a builder role. The bar is building and shipping production-grade AI integrations on a multi sprint cadence and the field signal you generate flows straight into the Connect AI roadmap.

Why This Role Matters:

The Forward Deployed Engineer is the hands-on force that turns CData’s Connect AI platform into real, working solutions inside customer environments. The FDE works directly with enterprise teams, and builds and ships production-grade integrations, connecting complex data systems, enabling governed access, and ensuring agent workflows perform reliably at scale. This role is critical to delivering tangible customer outcomes. FDEs ensure customers move from AI experimentation to real business impact. At the same time, the patterns, code, and insights the FDE generates in the field feeds directly back into the product, improving the platform and accelerating future deployments.

Location(s): Remote, U.S. (EST or West Coast Preferred)

Key Duties & Responsibilities:

Responsibilities include but are not limited to:

Embed and deliver in customer environments

• Embed with customer teams to 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 the 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

• Build and deliver iterative solutions on a multi sprint cadence with weekly customer demos, validation checkpoints, and AI workflow refinement
• Own deployment health for your engagements, monitor MCP performance, troubleshoot agent accuracy, and ensure a smooth Customer Success handoff
• Triage and resolve production issues with appropriate escalation to the architect or product team

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 from your engagements, code snippets, deployment recipes, and troubleshooting notes that compound across the FDE team

Qualifications

Must Haves:

• 3–6 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
• Has explained technical concepts to non-technical stakeholders and held the room
• 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

Travel Required: Up to 50%.

US Only: The typical base pay range for this role across the US is $150,000–$175,000 per year. The actual range may vary depending on specific locations. In the areas we're looking to hire within Eastern Time and West Coast markets, we expect the base pay range for this role to be $150,000–$175,000, depending on experience and qualifications.

Benefits & Perks / What you’ll Get: 

• As part of our comprehensive benefits offerings, we provide Medical, Dental, and Vision plans with company-paid insurance premiums 
• Health Saving Account offering with company contribution to help mitigate increasing health costs  
• Flexible Savings Account and Dependent Care FSA  
• Generous 20-day PTO and 11 paid holidays  
• 401k with 100% company match up to 6% of contribution 
• A remote-friendly, high-trust culture that empowers collaboration, celebrates curiosity, and encourages innovation 
• Work closely with your manager to define professional development and learning opportunities that match your career goals