Lead technical customer programs from kickoff through deployment and ongoing support while coordinating cross-functional teams. Manage project plans, resolve blockers, and ensure clear communication of risks and progress to stakeholders.
Lead, coach, and develop a team of Customer Reliability Engineers while serving as the first escalation point for technical and customer issues. Own a portfolio of customer accounts, diagnose facility issues, standardize team workflows, and partner with Product to improve tools and processes.
You will lead engineering efforts for connectivity projects, designing and building secure integrations that ingest telemetry and system data across diverse customer environments. Additionally, you will collaborate with cross-functional teams to turn one-off integrations into reusable product capabilities while mentoring engineers and ensuring operational excellence.
You will act as the technical relationship owner for deployed sites, managing post-implementation support and diagnosing facility anomalies. You will collaborate with cross-functional teams to drive product adoption and define requirements based on customer needs.
Manage a portfolio of customer accounts after implementation, monitoring Prism Insights to identify, triage, and diagnose facility issues and communicating findings to customer operations teams. Support customer adoption, document account findings, translate customer needs into product requirements, and collaborate with technical teams to develop scalable solutions.
You will act as a subject matter expert to operationalize and scale AI-powered control systems for enterprise data center customers. This involves creating facility models, defining product requirements, and collaborating with data science and product teams to ensure successful deployments.
You will operationalize and scale AI-powered control solutions for enterprise data center customers by configuring models and commissioning systems. Additionally, you will provide ongoing technical support, lead implementation projects, and act as a subject matter expert for both internal teams and clients.
You will operationalize and scale AI-powered control solutions for enterprise data center customers by configuring models and commissioning systems. Additionally, you will provide ongoing technical support, troubleshoot performance issues, and act as a subject matter expert for both internal teams and customers.
Design, implement, and evaluate model-based reinforcement learning agents and planning-based controllers for industrial control systems. Develop learned dynamics and world models while mentoring Research Engineers to translate research into practical production outcomes.
Lead a team of Solutions Engineers and Technical Program Managers to drive operational excellence and technical vision. Ensure seamless project execution, manage customer relationships, and influence product requirements based on technical engagements.
You will own the research, behavioral quality, and applied intelligence layer of agentic products, including reasoning patterns, prompts, and evaluation systems. You will partner with cross-functional teams to ensure agents are reliable, interpretable, and aligned with industrial operational needs.
The Senior Data Scientist will own a portfolio of customer deployments, proactively identifying performance issues and diagnosing system failures. They will also encode operational expertise into AI logic, validate model performance, and collaborate with cross-functional teams to drive impact.
Design and implement physics-based simulation models for thermodynamic and fluid systems while collaborating with AI researchers to integrate these simulators into reinforcement learning pipelines. Validate simulation models against real-world data and contribute to the development of scalable, reusable simulation tools.
Lead the design and implementation of infrastructure for deploying and operating control software within customer-controlled networks. Collaborate with cross-functional teams to turn site-specific constraints into reusable platform capabilities for installation, configuration, and monitoring.
You will lead the design and implementation of systems to make Phaidra’s platform capabilities available on Azure. This involves building reusable platform components, establishing deployment workflows, and ensuring reliability, security, and observability across Azure environments.
You will build and operate the Azure platform used by product and AI engineering teams, owning components from implementation through production. This involves creating reusable infrastructure, deployment workflows, and developer-facing automation to support Phaidra's growth.
Design, implement, and evaluate model-based reinforcement learning agents and planning-based controllers for industrial control systems. Develop learned dynamics and world models while mentoring research engineers to translate research into practical production outcomes.
You will operationalize and scale AI-powered control solutions for enterprise data center customers by configuring systems and creating facility models. Additionally, you will provide ongoing technical support, troubleshoot control systems, and collaborate with data science and product teams to define requirements.
You will lead the deployment, commissioning, and tuning of AI-powered control systems for industrial data center customers. Additionally, you will act as a technical expert, collaborating with data scientists and product teams to define requirements and provide ongoing support for deployed solutions.
Lead the product strategy and roadmap for Prism to establish it as the agentic operating platform for data centers. Partner with the CPO and cross-functional teams to translate customer pain into technical requirements and drive the platform from a point solution to a comprehensive intelligence layer.
Own the end-to-end delivery of complex, large-scale customer programs for AI-powered industrial control systems. Lead program strategy, manage executive-level communication, and collaborate with engineering teams to ensure successful deployment and customer satisfaction.
The engineer will act as the subject matter expert, modeling customer facilities for AI ingestion using Phaidra's platform and collaborating with Data Scientists to define product requirements based on customer needs. They will also work to ensure automated tools enable scaling the solution across thousands of customers.
Phaidra creates AI-powered control systems for the industrial sector, enabling facilities to automatically learn and improve over time. The team focuses on applying AI to complex industrial problems and fostering collaboration among domain experts.
