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Salary: USD 190,000 - 215,000 / annual
Crusoe is a vertically integrated AI infrastructure company building modular data centers (Spark and Spark-Liquid product lines) powered by an energy-first approach. The company owns and operates the full stack from electrons to tokens to power large-scale AI workloads.
You will serve as the Senior Staff Applications Engineer for Spark, owning the technical qualification framework that determines whether sites, partnerships, and commercial opportunities are viable for deployment. You are the point of contact for hard product questions and deliver authoritative technical verdicts on fit.
Key responsibilities include:
**Product Authority & Opportunity Qualification**
- Build and maintain standardized screening criteria, scoring models, decision thresholds, and report formats defining Spark viability
- Enable the Energy Development Group (EDG), business development, and partner teams to apply the framework independently on routine opportunities
- Serve as escalation point for undefined sites, non-standard configurations, and contested calls; deliver clear fit/conditional fit/no-fit verdicts with engineering rationale
- Turn around escalated feasibility assessments in days, not weeks
- Identify deviations from standard Spark configuration, quantify engineering cost and schedule impact, and route to responsible disciplines
- Evaluate technical fit for non-standard applications (edge deployments, distributed energy, co-located industrial, third-party colocation)
- Feed recurring field constraints back to Spark design engineering and R&D as prioritized product requirements
**Site & Partner Engagement**
- Serve as Spark's dedicated technical counterpart to EDG across the full site pipeline
- Evaluate candidate sites against Spark module requirements (power, thermal, civil, physical interface)
- Conduct site walks with EDG, developers, and utility counterparties; convert observations into product requirements and risk registers
**Technical Communication & Diligence**
- Provide technical inputs for financial modeling (module configuration, power/cooling assumptions, site-specific efficiency and derate factors)
- Translate multi-discipline engineering tradeoffs into clear go/no-go frameworks for commercial and executive stakeholders
Your judgment about where this product can be applied—not the design of the product itself—converts the pipeline into deployable capacity. Spark is on a path to deploy hundreds of megawatts, and every megawatt begins as an unqualified site on a map.
**Requirements:**
- 10+ years of progressive engineering experience in data center infrastructure, power generation/utility interconnection, industrial capital projects, or modular/containerized systems
- Working fluency across data center infrastructure disciplines: electrical (MV/LV distribution, switchgear, transformers), mechanical/thermal (DLC, CDUs, heat rejection), civil/structural (foundations, seismic/wind loading, rigging)
- Track record of making feasibility calls from first principles under incomplete information, with direct accountability for recommendations carrying real capital consequences
- Proven ability to hold technical credibility with external developers, utilities, enterprise customers, and executives while keeping opportunities moving rapidly
- Ability to connect engineering decisions directly to $/MW, capex, PUE, and deployment schedules
- Demonstrated depth on a specific engineered product or platform where you were the authoritative source on capabilities and limits
- Relentless technical rigor, comfort with ambiguity, safety-first culture, judgment to say no early, discipline to make calls with incomplete information
- Bachelor's degree in Electrical Engineering, Mechanical Engineering, or closely related engineering discipline
**Bonus:**
- Experience with modular, containerized, or prefabricated infrastructure product lines
- Familiarity with agency certification and AHJ coordination for modular electrical equipment across varied jurisdictions
- Deep familiarity with energy development, interconnection processes/queues, and behind-the-meter site configurations
