About CData Software, Inc.

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.

Principle 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 an architect who can design that solution inside the customer's environment.

We're hiring an Architect, Forward Deployed Engineering (FDE) to be the senior technical leader inside our most strategic enterprise engagements. You'll embed with customers to translate AI ambitions into production architectures on CData Connect AI, our managed MCP platform, and the broader CData stack — designing how data, AI, and governance fit together end-to-end. You'll be the technical voice the customer trusts and the field-level expert whose patterns shape what we build next in product.

This is a senior IC role with significant leverage. You won't manage people directly, but you'll mentor FDEs on each engagement, set the technical bar for the work, and partner closely with the FDE Director and Product leadership on the patterns that turn field wins into reusable IP.

Why This Role Matters:

The Architect, Forward Deployed Engineering works directly with strategic customers and designs how AI, data and governance come together end-to-end to ensure deployments on Connect AI are scalable, secure, and deliver measurable outcomes. This role goes beyond solution design. By shaping architectures, defining best practices, and identifying product gaps in real time, the Architect directly influences the evolution of the Connect AI platform. Their work creates patterns that accelerate future deployments, strengthen technical credibility with enterprise buyers, and reduce time to value across engagements.

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

Key Duties & Responsibilities:

Responsibilities include but are not limited to:

Lead customer engagements

• Run technical discovery workshops with customer architects, data leaders, and AI teams, mapping data sources, MCP Workspace scoping, and agent tooling requirements
• Own the scoping for AI deployments with clear acceptance criteria around agent accuracy, data coverage, and governance
• Translate complex AI + data concepts into executive-ready architecture proposals; defend trade-offs to CxO-level stakeholders

Architect AI data connectivity end-to-end

• Design solutions across Connect AI’s 350+ sources covering MCP server configuration, semantic context modeling, and governance integration
• Architect agent orchestration using Connect AI Toolkits, defining which data, schemas, and actions each agent can access in production
• Design governed access patterns for AI agents: RBAC, OAuth 2.1, semantic scoping, and audit-trail requirements
• Define AI Best practices using agents, skills and LLMs to drive successful customer outcomes

Shape the evolution of the Connect AI platform through real-world deployments

• Identify architectural and product gaps during live enterprise engagements and partner with Product and Engineering to define scalable solutions
• Author technical specifications and implementation recommendations for Connect AI enhancements, including both features and core architectural improvements
• Build reusable reference architectures, deployment patterns, and MCP blueprints that reduce implementation friction and accelerate future customer deployments
• Translate recurring customer deployment challenges into scalable platform capabilities and architectural standards

Elevate the team

• Mentor FDEs on AI integration patterns, semantic data modeling, and customer-facing technical delivery
• Serve as the first level technical escalation point for customer engagements
• Partner with Product, Engineering, Solutions Engineering, and Customer Success on architectural standards
• Codify field patterns into shared assets, playbooks, templates, sample agents, that the broader team can reuse (SE, CS, support etc.)

Qualifications

Must Haves:

• 7+ years as a Solutions Architect, Principal SE, Forward Deployed Engineer, or Technical Lead at a data platform, AI, or enterprise SaaS company
• Has built and shipped production AI applications — not just prototypes
• Worked on a SaaS Platform in an Architect Profile (or closely aligned role)
• Customer-facing track record with senior technical buyers and architecture review boards
• Strong AI/ML literacy: LLM capabilities, agentic architectures, RAG patterns, prompt engineering, and when to apply each
• Able to define Multi-tenant Architectural patterns and security objectives
• Hands-on enterprise data integration: SQL, ETL/CDC pipelines, API design, ODBC/JDBC, and multi-source connectivity
• Able to design governed data access for AI agents — RBAC, OAuth 2.1, semantic scoping, and audit-trail requirements
• Experience with modern data stacks (Snowflake, Databricks, Salesforce) and cloud-native deployment patterns
• Ability to translate complex AI + data concepts into executive-ready architecture proposals
• High agency; comfortable being the senior technical voice in the room with the customer
• Experience mentoring junior engineers without requiring direct reporting relationships

Nice to Have:

• Direct experience with the MCP protocol and AI agent frameworks (LangChain, CrewAI, Copilot Studio)
• Prior experience as an FDE or in a similar embedded customer-facing engineering role

Travel Required: Up to 50%

US Only: The typical base pay range for this role across the US is $175,000–$240,000 per year. The actual range may vary depending on specific locations. In the areas we’re looking to hire within Pacific Time Zone markets, including California, Washington, Oregon, and other West Coast locations, we expect the base pay range for this role to be $175,000–$240,000, 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