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Roles
Compensation
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.
- Salary period
- unclear
- Location basis
- specific locations
Benefits
- 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
Tech stack
OData
Snowflake
Copilot Studio
Databricks
Python
MCP protocol
ODBC
RBAC
SQL
CrewAI
XML
OAuth 2.1
JDBC
CData Connect AI
MCP
LangChain
C#
Salesforce
JSON
Java
Required
PythonJavaC#SQLREST APIsODBC/JDBCJSON/XMLRBACOAuth 2.1
Nice to have
MCP protocolLangChainCrewAICopilot StudioSnowflakeDatabricksSalesforce
Location
Remote, U.S. (EST or West Coast Preferred)
Work setup
- Employment
- full-time
- Level
- Principal
- Remote policy
- Remote with possible some travel
- Remote scope
- unclear
- Timezones
- EST, West Coast
- Travel
- Possible some travel
- Visa
- No
- Authorization
- Applicants must be currently authorized to work in the United States on a full-time basis.
Role details
Responsibilities
- 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
- 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
- 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
- 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
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
- 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
Application
Apply now
- Portfolio
- unclear
- GitHub
- unclear
- Cover letter
- unclear
- Apply flow
- ats
Description
Remote with possible some travel
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