Full-Time

Senior Solutions Engineer

Energy/Oil & Gas

DataRobot

DataRobot

501-1,000 employees

Enterprise AI platform automating ML lifecycle

No salary listed

Houston, TX, USA

In Person

Must be willing to travel up to 25% to customer meetings and field sites.

Bachelor's, Master's, PhD

Category
Sales & Solution Engineering (2)
,
Required Skills
Forecasting

Get referred to DataRobot

See people who can refer or advise you

Requirements
  • 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)
  • 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
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
Desired Qualifications
  • Advanced degree in a technical or analytical field, or in petroleum/chemical/mechanical engineering or geoscience
  • Experience supporting AI/ML or advanced analytics sales, ideally for industrial or energy use cases
  • Familiarity with oil & gas data and systems—industrial time-series/sensor data, OT/SCADA and historian platforms, and common upstream/midstream/downstream workflows
  • Demonstrated success supporting sales pursuits 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

DataRobot provides an enterprise AI platform that automates the end-to-end machine learning lifecycle, from data preparation to model deployment and management. It uses Automated Machine Learning to try many algorithms in parallel, then handles deployment, monitoring, and governance, with options for both code-first and no-code workflows and support for generative AI features. The platform runs in the cloud or on-premises and offers MLOps, model safety, and governance tools to manage models in production. Its goal is to democratize AI by making advanced machine learning accessible to a broad range of users while ensuring governance and safety at scale.

Company Size

501-1,000

Company Stage

Series G

Total Funding

$1.1B

Headquarters

Boston, Massachusetts

Founded

2012

Get referred to DataRobot

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • March 2026 Nebius partnership sells validated NVIDIA infrastructure for production agents.
  • July 2026 governance beyond cloud targets regulated buyers, including sovereign and air-gapped environments.
  • June 2026 enterprise momentum included Dell, Nebius, and Aon partnerships across hybrid deployments.

What critics are saying

  • The Information reported 7% layoffs in November 2025, signaling cost pressure and slowing growth.
  • Executives including CEO Dan Wright and CFO Damon Fletcher departed in 2025, weakening execution.
  • Hyperscalers and open-source stacks commoditize agent platforms, squeezing DataRobot into niche regulated deployments.

What makes DataRobot unique

  • DataRobot’s July 2025 Agent Workforce Platform runs across cloud, on-premises, and air-gapped environments.
  • June 2026 Gartner named DataRobot a DSML Leader for the third consecutive year.
  • DataRobot pairs governance, monitoring, and deployment into one enterprise stack with NVIDIA.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Paid Holidays

Paid Parental Leave

Global Employee Assistance Program (EAP)

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-1%
Associated Press
Jul 2nd, 2026
DataRobot extends AI governance beyond cloud to on-premises and air-gapped environments

DataRobot has launched an enterprise AI governance platform that extends beyond cloud environments to on-premises, edge, air-gapped and sovereign systems. The solution addresses fragmentation in AI governance, where platform and cloud vendors typically only govern within their own boundaries. The platform operates across three layers: AI and agentic governance with real-time moderation for bias and compliance, IT governance with granular permissions and end-to-end lineage tracking, and infrastructure governance for cost optimisation across deployment environments. It aligns with the NIST AI Risk Management Framework and EU AI Act. Co-engineered with NVIDIA and validated across Dell and Nebius infrastructure, the DataRobot Agent Workforce Platform enables consistent policy enforcement and compliance documentation regardless of where AI agents operate or who built them.

DataRobot
Mar 18th, 2026
DataRobot and Nebius partner to bring enterprise AI agents to production at scale on NVIDIA AI infrastructure.

DataRobot and Nebius partner to bring enterprise AI agents to production at scale on NVIDIA AI infrastructure. March 18, 2026 - BOSTON - DataRobot and Nebius today announced a strategic partnership that pairs the DataRobot Agent Workforce Platform, co-engineered with NVIDIA, with purpose-built AI cloud infrastructure for the modern enterprise. This solution delivers a fully optimized and validated AI factory, combining Nebius's dedicated NVIDIA-GPU based infrastructure with the DataRobot platform to build, deploy, monitor, and govern agents seamlessly - enabling enterprises to take agents to production within days versus months while bypassing the operational complexity of traditional hyperscalers. The partnership addresses a real operational gap. Running AI agents requires sustained inference performance, runtime governance, and infrastructure that behaves predictably as demand grows. Due to performance and cost variability, enterprises are increasingly evaluating infrastructure designed specifically for AI rather than retrofitted general-purpose clouds. Together, DataRobot and Nebius are addressing this structural shift by delivering a validated, AI-optimized stack that pairs the DataRobot Agent Workforce Platform with Nebius's purpose-built AI cloud and NVIDIA's GPUs and open software unlocking scalable, high-performance agentic AI beyond conventional cloud constraints. "When agents run continuously, performance variability and unpredictable costs create operational risk. By partnering with DataRobot and building on NVIDIA's AI foundation, we're providing a validated deployment environment on Nebius AI Cloud that delivers consistent latency, predictable pricing, and the performance required for sustained agent workloads," said Laurelle Roseman, VP of Global Partnerships, Nebius. The initiative allows DataRobot to deploy NVIDIA GPU-backed inference workloads - such as custom models and agent execution services - directly on Nebius managed Kubernetes, integrating agent intelligence and governance with high-performance NVIDIA infrastructure purpose-built for AI. "As we expand our use of AI, access to scalable infrastructure and the ability to operationalize models efficiently are critical. DataRobot and Nebius are helping simplify how we deploy and manage AI solutions in production, which is an important step as we continue building more AI-driven capabilities across the business," said Vijay Raghavendra, GEICO's Chief Product and Technology Officer. By eliminating noisy-neighbor overhead found in legacy clouds, this joint solution offers bare-metal-like performance with the low latency and predictable throughput required for always-on agents. Powered by the NVIDIA Hopper and NVIDIA Blackwell-generation data-center GPUs and secured by NVIDIA NeMo Guardrails, the platform provides a clear path to have AI to operate as a dependable, production-grade system within the enterprise. This co-designed stack delivers enterprise-grade capabilities without the lock-in, cost volatility, or architectural limits and premium costs of traditional providers - allowing organizations to scale their agent workforce with absolute confidence. "Agentic AI is only valuable if it works every time, not just in demos. This collaboration addresses the industry's biggest blind spot: operationalizing agents safely and predictable costs at scale. Together with Nebius and NVIDIA, we're delivering a validated AI factory that enterprises can trust in production - not tied to a single cloud, and not compromised by infrastructure uncertainty," said Debanjan Saha, CEO of DataRobot. "Enterprises are rapidly evolving from isolated AI projects to always-on agentic systems that can be trusted in production. By combining the DataRobot Agent Workforce Platform with Nebius' dedicated AI cloud and NVIDIA AI infrastructure, organizations can deploy a validated AI factory that delivers low-latency performance, predictable costs, and the governance required to safely scale an agent workforce across the business," said John Fanelli, vice president, AI Software, NVIDIA. About DataRobot DataRobot empowers AI teams to deliver the agentic workforce of the future. Its platform enables organizations to create and scale AI agents that integrate directly with business processes - driving efficiency, transforming operations, and delivering real results. With built-in governance and safeguards, DataRobot help enterprises deploy AI securely and confidently. For more information, visit its website and connect with DataRobot on LinkedIn. About Nebius Nebius, the AI cloud company, is building the full-stack platform for developers and companies to take charge of their AI future - from data and model training to production deployment. Founded on deep in-house technological expertise and operating at scale with a rapidly expanding global footprint, Nebius serves startups and enterprises building AI products, agents, and services worldwide. Nebius is listed on Nasdaq (NASDAQ: NBIS) and headquartered in Amsterdam. For more information. please visit www.nebius.com.

Techzine
Mar 16th, 2026
Okta launches platform to secure AI agents

Okta launches platform to secure AI agents. Okta for AI Agents is a platform that treats AI agents as full-fledged, non-human identities. It provides organizations with tools to discover agents, manage access, and immediately revoke access tokens. Okta for AI Agents is designed to help organizations answer three fundamental questions: where are my agents, what can they connect to, and what are they allowed to do? The impetus is a growing security problem. Only 22 percent of organizations treat AI agents as independent, identity-bearing entities, while 88 percent have already dealt with suspected or confirmed security incidents involving AI agents. But the problem extends beyond known agents. Ninety percent of AI usage occurs through unauthorized personal accounts, with an average of 223 shadow AI incidents per month. Okta addresses this with Shadow AI Agent Discovery, a feature that automatically detects when employees link AI agents to corporate applications. Three pillars for secure AI agents. The platform is built on three pillars. For registration and visibility, Okta is expanding its Okta Integration Network with dedicated support for platforms such as Boomi, DataRobot, and Google Vertex AI. Currently, that network already includes 8,200 integrations. Agents are registered as non-human identities in the Universal Directory, with a lifecycle spanning from onboarding to decommissioning. The second pillar is access management. An Agent Gateway serves as a central control plane for all connections between agents and resources: MCP connections, tools, APIs, and databases. Agent credentials are automatically rotated via a secure vault, ensuring they never appear in plain text or logs. The third pillar is the ability to revoke access immediately. Through Universal Logout, Okta can deactivate all access tokens if an agent deviates from its intended mission. All activity, including tool calls and authorization decisions, is forwarded to the organization's SIEM.

Technology AI Insights
Jul 31st, 2025
DataRobot Launches Agent Workforce Platform to Operationalize AI Agents at Scale

DataRobot launches Agent Workforce Platform to operationalize AI agents at scale.

RTInsights
Jul 12th, 2025
Real-time Analytics News for the Week Ending July 12

DataRobot's syftr, integrated with Cerebras' AI inference performance, delivers a toolchain for production-grade agentic apps.