Senior Systems Engineer
Crusoe is an AI infrastructure and cloud computing company. It provides GPU cloud capacity, managed AI services, inference, fine-tuning, data centers, and energy infrastructure for AI developers and enterprise customers.
Maintainer signals as of 8/23/2026
Funding history
Projects
About Crusoe, Inc
Crusoe designs, builds, and operates energy-first AI infrastructure, including data centers, GPU cloud computing, and modular AI factories. Crusoe Cloud provides GPU clusters, managed Kubernetes and Slurm, storage, networking, observability, managed inference, serverless fine-tuning, and model deployment through Crusoe Intelligence Foundry. Its customers include AI startups, enterprises, and organizations developing training, inference, analytics, and other compute-intensive workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Design and implement agentic AI workflows and autonomous agents across enterprise systems. Build unified data layers, integrations, APIs, connectors, deployment pipelines, and lifecycle systems; embed security and compliance guardrails; create reusable tooling; mentor internal teams; and evaluate emerging AI technologies.
Requirements
- 10+ years of software engineering experience
- 3+ years in AI/ML or AI application development
- Strong proficiency in Python and API development, including REST, GraphQL, and webhooks
- Hands-on experience with Workato, MuleSoft, Zapier, or similar enterprise integration platforms
- Experience with LLM APIs such as OpenAI, Anthropic, or Google Gemini
- Understanding of agentic architectures, RAG patterns, and prompt engineering
- Experience designing scalable distributed systems in AWS, GCP, or Azure
- 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, SOC 2, and GDPR
Responsibilities
- Design and implement agentic AI workflows
- Build autonomous agents that orchestrate enterprise systems
- Architect and integrate a unified data layer
- Develop integrations, APIs, and custom connectors
- Implement MCP connectors and model-agnostic orchestration patterns
- Design deployment pipelines and lifecycle management systems for AI agents
- Embed security, data privacy, and compliance guardrails
- Create reusable templates, frameworks, and tooling
- Mentor internal teams through code reviews, training, and technical enablement
- Evaluate emerging AI technologies and prototype capabilities
Benefits
- Competitive compensation
- Equity packages
- Restricted Stock Units
- Paid time off
- Paid holidays
- Leave of absence programs
- Comprehensive health insurance
- Dental insurance
- Vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance
- Short-term disability insurance
- Long-term disability insurance
- Professional development
- Tuition reimbursement
- Mental health and wellness support
- Commuter benefits for parking and transit
- Cell phone stipend
- 401(k) retirement plan with company match up to 4% of salary
- Volunteer time off
- Global travel insurance and emergency assistance
- Daily meals allowance
- Location-specific perks and programs
