Role Description We are seeking a Manager IT Security Engineering with strong SOC experience to implement, operate, and optimize enterprise security platforms across cloud, identity, endpoint, network, and vulnerability management domains. This role supports immediate security initiatives and serves as an L3 escalation point within a rotating on-call model. Key Responsibilities - Platform Management: Implement, configure, upgrade, document, and troubleshoot security platforms, including: - Microsoft Sentinel (SIEM/SOAR) - Microsoft Defender (XDR/DLP) - Microsoft Purview - Entra ID - Microsoft 365 Security - Tenable (including Cloud TVM) - Tanium - Delinea (PAM) - GitHub Security - Google Security Command Center (SCC) - Palo Alto Firewalls - SIEM & Logging: Lead enterprise-wide logging implementation and SIEM data onboarding. - Vulnerability Management: Implement vulnerability and cloud TVM solutions and integrate with asset/CMDB data. - Operational Excellence: Develop cyber security health monitoring and detection quality improvements. - Network Security: Perform firewall rule reviews, cleanup, and tightening. - Incident Response: Act as L3 SOC support for advanced investigations and incident response. - Collaboration: Partner with IT and infrastructure teams; participate in change control processes. - Innovation: Apply AI-assisted approaches to investigation and security operations. - Availability: Participate in a rotating L3 off-hours on-call schedule. Qualifications - Minimum of 5–7 years of experience in Cyber Security Engineering or Security Operations (SOC), with a proven track record in an L3 or senior technical lead capacity. - Expert-level proficiency in implementing and managing the Microsoft security ecosystem, specifically Microsoft Sentinel (SIEM/SOAR) and Microsoft Defender (XDR). - Strong hands-on experience with Microsoft Entra ID, Microsoft 365 security configurations, and Microsoft Purview. - Demonstrated experience operating enterprise vulnerability management tools (e.g., Tenable, Tanium) and integrating them with CMDB/Asset management workflows. - Experience with Palo Alto Firewalls, including rule review, policy optimization, and troubleshooting. - Advanced knowledge of incident response lifecycles and the ability to lead complex investigations as a senior escalation point. - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. Preferred - Experience in Renewable Energy, Automotive (EV), or Semiconductor industries. - Strong ability to communicate complex technical risks to executive leadership and board members. - Familiarity with export control regulations and international intellectual property protection. - Visionary strategic thinker able to navigate rapidly evolving global energy storage markets. Benefits - Immediate medical, dental, vision and prescription drug coverage - Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more - Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more - Vehicle discount program for employees and family members and management leases - Tuition assistance - Established and active employee resource groups - Paid time off for individual and team community service - A generous schedule of paid holidays, including the week between Christmas and New Year’s Day - Paid time off and the option to purchase additional vacation time.

• Lead and support a team of research engineers and machine learning engineers, helping them grow and do their best work • Define and deliver the engineering roadmap, balancing fast experimentation with production readiness • Build and scale machine learning infrastructure, including training pipelines, experimentation systems, and shared tooling • Partner with research scientists, product managers, and platform teams to bring ideas from research into user-facing features • Improve engineering practices in a research environment, including testing, reproducibility, and deployment workflows • Support the transition of research prototypes into reliable, scalable production systems • Contribute to strategic planning and align engineering work with broader company priorities

• Lead and support a team of research engineers and machine learning engineers, helping them grow and do their best work • Define and deliver the engineering roadmap, balancing fast experimentation with production readiness • Build and scale machine learning infrastructure, including training pipelines, experimentation systems, and shared tooling • Partner with research scientists, product managers, and platform teams to bring ideas from research into user-facing features • Improve engineering practices in a research environment, including testing, reproducibility, and deployment workflows • Support the transition of research prototypes into reliable, scalable production systems • Contribute to strategic planning and align engineering work with broader company priorities

• Lead the organizational and technical direction of the team: proactively share context to help the team connect the dots of their work with broader company initiatives • Build a robust team by attracting top talent, mentoring individuals and regularly providing feedback • Nurture a culture of technical quality from design, through code review, to production • Collaborate with internal teams and cross-functional partners to gain agreement by developing and communicating a clear and impactful vision and priorities for the team • Implement an execution framework that detects problems early and enables thoughtful planning, tracking and reporting on the work of the team