Celigo
Forward Deployed AI Engineer
About this role
Celigo seeks a Forward Deployed AI Engineer to embed within enterprise customers and drive adoption of AI-powered integration and automation solutions. You'll conduct discovery workshops, design intelligent agents and agentic workflows, and build production-grade solutions using Celigo's AI Studio and MCP server orchestration.
What you'll do
- Lead discovery workshops and strategy sessions with executive teams to identify AI opportunities and translate them into actionable project plans
- Design and develop AI agents, agentic workflows, and intelligent prompts using Celigo's AI capabilities and frontier LLM models
- Set up, configure, and maintain MCP servers for scalable integration runtime environments
- Design, manage, and govern APIs including endpoints, authentication, versioning, and security best practices
- Co-build solutions alongside customers and partners, delivering POCs and MVPs from concept to deployment in days
- Provide end-to-end testing, go-live support, knowledge transfer, and ongoing advisory services to enterprise clients
What they're looking for
- Prompt engineering and frontier LLM models (ChatGPT, Claude, etc.)
- API integration, lifecycle management, versioning, and governance
- ERP system integration (NetSuite, Acumatica, Dynamics, SAP)
- Cloud/SaaS platform integration (Salesforce, Shopify, AWS)
- Data transformation (JSON, XML, CSV, EDI, mapping, normalization)
- Agentic architectures and MCP server orchestration
- iPaaS and middleware architecture patterns
- Client-facing communication and technical consulting
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Celigo
Celigo builds data infrastructure and analytics solutions that transform raw data into reliable, well-documented data models serving as a single source of truth for organizations. The company is hiring Analytics Engineers to design scalable data architectures using modern tools like dbt/Coalesce and support data-driven decision-making across product, finance, and go-to-market functions.
- Website
- celigo.com
Likely interview questions
- Describe your experience designing and deploying production AI agents—what challenges did you encounter and how did you solve them?
- Walk us through how you've approached prompt engineering and LLM integration to solve a complex business problem.