DataRobot

Senior Solutions Engineer- Energy/Oil & Gas

Vaga remota de Solutions Engineering com fit claro de localização do candidato.

Publicada25 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Senior Solutions Engineer- Energy/Oil & Gas

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Key Responsibilities:

Business-to-Technical Translation: Partner with sales teams to understand operators' strategic priorities and technical constraints; map those to DataRobot capabilities, with tailored messaging for energy personas (CIO/CTO, Chief Data Officer, VP of Digital/Digital Transformation, reservoir and production engineering leaders, plant and reliability managers, HSE leadership, and OT/process-control practitioners).
Demo Execution & Use Case Framing: Deliver engaging, outcome-oriented demos grounded in oil & gas use cases, such as predictive maintenance on rotating equipment (ESPs, compressors, turbines), production optimization and decline-curve analysis, predictive emissions and methane-leak detection, drilling optimization and ROP prediction, refinery yield and energy optimization, and demand forecasting, for both new prospects and existing customers; shape and refine use cases based on asset maturity, data availability, and strategic alignment.
Solution Design & Deployment Readiness: Define key technical requirements and recommend deployment models that fit energy operating realities—on-prem, edge, hybrid, and air-gapped or low-connectivity field deployments, and advise on readiness of data to ensure quick time-to-value for new and expansion opportunities.
Compliance & Security Alignment: Support conversations around AI governance, data security, model transparency, and responsible AI in alignment with industry and regulatory context relevant to energy operators (process-safety and critical-infrastructure expectations, OT/IT segmentation, and emerging AI governance standards).
Cross-Functional Feedback Loop: Provide structured feedback on energy-sector needs, procurement hurdles, and technical blockers to Product, Marketing, and Enablement teams, ensuring DataRobot's offerings remain relevant for upstream, midstream, and downstream buyers.
Sales Collaboration: Act as a trusted advisor across the sales team by supporting Account Executives, and Engagement Director with the technical knowledge and assets that advance AI adoption in oil & gas accounts.

Knowledge, Skills and Abilities:

Strong ability to translate GenAI and ML platform capabilities into the language of energy operations and the metrics operators are measured on.
Familiarity with oil & gas data and systems—industrial time-series/sensor data, OT/SCADA and historian platforms, and common upstream/midstream/downstream workflows—strongly preferred.
Demonstrated success supporting sales pursuits (new logos and account expansion) with technical expertise and solution design.
Excellent communication and demo skills; proven ability to present complex AI concepts in a clear, value-driven manner to both business leaders and technical stakeholders, including engineers and OT practitioners.
Comfort working in a fast-paced environment with evolving product offerings and shifting priorities.

Knowledge, Skills and Abilities:

6–10 years of experience in customer-facing AI engagement, pre-sales engineering, or technical consulting within software/SaaS, with direct experience in oil & gas, energy, or utilities preferred.
Bachelor's degree in a technical, analytical, or business-related field (or equivalent experience); advanced degree in a technical or analytical field, or in petroleum/chemical/mechanical engineering or geoscience, a plus.
Experience supporting AI/ML or advanced analytics sales, ideally for industrial or energy use cases.
Ability to travel up to 25% on average to customer meetings, workshops, industry conferences (e.g., energy-sector events), and field/asset sites, which may include travel to operational facilities.