
201 - 500 employees
☁️ SaaS
🏢 Enterprise
🔌 API
💰 $350M Private equity on 2024-07
SaaS • Enterprise • API
CData Software is a provider of enterprise-grade data connectivity and integration software that delivers live, contextual, and secure access to hundreds of on-premises and cloud data sources. Its platform includes standards-based drivers (ODBC, JDBC, ADO. NET), language connectors (Python, Java), API server capability, ETL/ELT and real-time sync tools, and embedded connectors for software vendors. CData also offers AI-native connectivity and a semantic layer to enable AI tools and agents to access governed, context-rich data in real time.
🕒 May 13
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201 - 500 employees
☁️ SaaS
🏢 Enterprise
🔌 API
💰 $350M Private equity on 2024-07
SaaS • Enterprise • API
CData Software is a provider of enterprise-grade data connectivity and integration software that delivers live, contextual, and secure access to hundreds of on-premises and cloud data sources. Its platform includes standards-based drivers (ODBC, JDBC, ADO. NET), language connectors (Python, Java), API server capability, ETL/ELT and real-time sync tools, and embedded connectors for software vendors. CData also offers AI-native connectivity and a semantic layer to enable AI tools and agents to access governed, context-rich data in real time.
• 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 • 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.)
• 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
• 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
Apply Now🕒 May 13
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