Senior Director, System Engineering & Intelligence, Global

About this role

About Nscale

Nscale is the vertically integrated AI cloud engineered for AI. We own and operate the full stack — energy, data centres, GPU superclusters, orchestration, and AI services — delivering high-performance infrastructure to AI-native companies, enterprises, and governments across Europe and the US. We are deploying GPU capacity at hyperscale, operating some of the densest, most advanced AI infrastructure in the world.
At Nscale, our Data Centre Systems Engineering team designs the systems, data, and intelligence that let us build and operate AI data centres at a speed and density traditional operating models were never designed for. We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you'll be contributing to building the technology that powers the future.
About the Role
Nscale's operational systems (BMS, DCIM, EPMS/SCADA, CMMS/EAM, ITSM, fabric and GPU telemetry) and equipment data were procured independently. Each works well on its own, but together they give overlapping and sometimes contradictory views of the same assets.
As Senior Director, System Engineering & Intelligence, you will bring that data centre insight together. You'll own the equipment digital thread — from product definition and procurement through commissioning and handover into maintenance — along with the telemetry and analytics foundation that lets the Nscale Operational Systems (NOS) act on our physical estate with confidence.
The goal is data centres that are measurably self-aware and progressively self-operating, where a site is declared ready based on evidence rather than judgement.
What You'll be Doing

• Set strategy and investment: own a costed, sequenced multi-year roadmap and investment portfolio across CMMS/EAM, PIM/PLM, integration, telemetry, and the data platform, starting with an assessment of which systems should be consolidated, retained, replaced, or newly instrumented.
- Own the asset master and governance: establish one canonical identity for every asset, along with taxonomy, hierarchy, configuration, and BOM standards, ensuring every critical data object has one system of record.
- Lead cleansing and validation-at-source programmes so governed lifecycle data replaces spreadsheets.
- Build the telemetry foundation: deliver a unified asset and topology model from grid connection down to GPU and network port, with OT/IT ingest (Modbus, BACnet, OPC UA, MQTT, Redfish, DCGM) and IEC 62443-aligned segmentation.
- Publish data-quality scores and agree single, shared definitions for PUE, WUE, capacity, stranded power, and availability.
- Make maintenance and reliability trustworthy: own the CMMS/EAM configuration baseline (criticality, PM strategy, spares, warranties) and controlled SOP/MOP/EOP libraries.
- Map condition data deterministically to assets so predictive maintenance raises work orders, not just reports.
- Move NOS intelligence toward autonomy: build anomaly detection, remaining-useful-life prediction, and thermal and power optimisation.
- Progress control loops through shadow, recommend-only, human-approved, and bounded-autonomous stages, each with explicit safety envelopes and engineering sign-off.
- Assure site readiness: turn commissioning (L1–L5) into data, set acceptance gates for handover, and score readiness quantitatively per hall and per site.
- Benchmark readiness across the portfolio so defects found on one build are designed out of the next.
- Act as the senior escalation point across Engineering, Procurement, Construction, Operations, Reliability, Platform, Finance, and HSE, and enforce supplier and OFCI data deliverables.
- Build and develop a high-performing team spanning lifecycle engineering, data science, and data engineering.

About You

• 15+ years of experience across engineering, asset management, enterprise systems, or industrial analytics, including 7+ years leading cross-functional programmes at director level or above.
- Ownership of a CMMS/EAM platform at scale (e.g. Maximo, SAP PM, Infor, Nuvolo), plus depth in master data, PIM/PLM, BOM, and configuration management.
- Proven delivery of analytics or ML on physical infrastructure (data centres, energy, utilities, heavy industry, or similar), including hands-on experience with messy BMS/SCADA/historian data.
- Experience taking models into control or decision loops, along with the safety, validation, and governance work that requires.
- Strong judgement on enterprise and data architecture, including ERP, integration, streaming, time-series storage, lineage, and Palantir Foundry or an equivalent platform.
- Experience with ITIL-aligned operations and controlled MOP, LOTO, and permit-to-work regimes in mission-critical environments.
- Credibility with both facilities engineers and software teams.
- A track record of building a function from scratch.
- Honesty and clarity with executives about uncertainty.

Nice to Have

• Knowledge of AI/HPC data centre plant, including liquid cooling, UPS, switchgear, and GPU and fabric telemetry.
- Familiarity with reliability standards such as RCM, FMEA, ISO 14224, and ISO 55000.
- Experience with digital twin or CFD-informed modelling.

- Experience with BIM/COBie handover.

• Background in energy and grid optimisation.

Why this role matters
This role turns a fragmented set of systems into a single, trusted source of truth for how Nscale's data centres are built, run, and improved. Success will be measured by:

• Fewer unplanned incidents, faster detection and diagnosis, and more interventions triggered by prediction rather than alarms.
- Improved PM compliance, MTTR, and spares fill rate.
- PUE/WUE gains and stranded capacity recovered.
- Cohesive analytics views across the data centre landscape.
- Fewer…