About the job
We’re seeking a Staff Enterprise AI Automation Engineer to play a key role in executing Crusoe’s 2026 Enterprise AI Strategy. In this role, you will design and build agentic AI systems that move the organization from simple information retrieval to orchestrated, multi-system automation. You’ll operate at the intersection of AI, enterprise systems, and integration platforms—building scalable agent workflows, enabling a citizen developer ecosystem, and establishing the technical foundations for an AI-powered operating model.
Responsibilities
- Designing and implementing agentic AI workflows using a modular, API-first architecture across platforms such as Workato ONE, Anthropic Claude, and Gemini.
- Building autonomous agents that orchestrate workflows across enterprise systems (e.g., Salesforce, Coupa, Slack, Google Workspace)
- Architecting and integrating a unified data layer that enables AI agents to access and act on data across siloed systems
- Developing integrations, APIs, and custom connectors that enable scalable AI orchestration across business platforms
- Implementing MCP (Model Context Protocol) connectors and model-agnostic orchestration patterns
- Designing deployment pipelines and lifecycle management systems for AI agents in production environments
- Embedding security, data privacy, and compliance guardrails into all AI implementations
- Creating reusable templates, frameworks, and tooling to support a Citizen Developer Program
- Mentoring internal teams through code reviews, training, and technical enablement programs
- Evaluating emerging AI technologies and prototyping next-generation capabilities to advance agentic maturity
Qualifications
Minimum
- 10+ years of software engineering experience, including 3+ years in AI/ML or AI application development
- Strong proficiency in Python and API development (REST, GraphQL, webhooks)
- Hands-on experience with enterprise integration platforms (e.g., Workato, MuleSoft, Zapier)
- Experience working with LLM APIs (OpenAI, Anthropic, Google Gemini, or similar)
- Deep understanding of agentic architectures, RAG patterns, and prompt engineering
- Experience designing scalable, distributed systems in cloud environments (AWS, GCP, or Azure)
- Strong knowledge of microservices, event-driven architecture, and integration design patterns
- Experience with CI/CD, infrastructure as code, and DevOps practices
- Understanding of data security, privacy, and compliance considerations (SOC 2, GDPR)
Preferred
- Experience deploying agentic AI systems in production environments
- Familiarity with iPaaS platforms (Workato preferred) and enterprise automation ecosystems
- Experience with Google Workspace or Microsoft 365 automation and extensibility
- Knowledge of Model Context Protocol (MCP) or similar interoperability standards
- Experience implementing AI governance frameworks in enterprise settings
- Background in infrastructure, energy, or high-performance computing environments
- Contributions to open-source AI projects or technical thought leadership