About The Role

Join Crusoe, a leading company in the AI and energy sectors, as a Senior Systems Engineer. In this role, you will be instrumental in executing Crusoe's 2026 Enterprise AI Strategy by designing and building agentic AI systems. You will work at the intersection of AI, enterprise systems, and integration platforms, creating scalable workflows and establishing the technical foundations for an AI-powered operating model. This position offers comprehensive health benefits, paid time off, a 401(k) matching program, and resources for mental wellness.

Design and build agentic AI systems that enable multi-system automation and orchestration.
Architect and integrate a unified data layer that allows AI agents to access and act on data across siloed systems.
Mentor internal teams through code reviews, training, and technical enablement programs, and create reusable templates and frameworks to support a Citizen Developer Program.
If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe
We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services
Experience working with LLM APIs (OpenAI, Anthropic, Google Gemini, or similar)
Strong proficiency in Python and API development (REST, GraphQL, webhooks)
Hands-on experience with enterprise integration platforms (e.g., Workato, MuleSoft, Zapier)
Deep understanding of agentic architectures, RAG patterns, and prompt engineering
Experience designing scalable, distributed systems in cloud environments (AWS, GCP, or Azure)
10+ years of software engineering experience, including 3+ years in AI/ML or AI application development
Understanding of data security, privacy, and compliance considerations (SOC 2, GDPR)
Experience with CI/CD, infrastructure as code, and DevOps practices
Strong knowledge of microservices, event-driven architecture, and integration design patterns
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

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