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DRS RADA is a global pioneer for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance. Provide professional and technological ownership of the enterprise application landscape, including architecture, standards, and the overall quality of APEX solutions across the organization. Key Responsibilities:
* Serve as the professional owner of the enterprise application architecture, including ERP, MES, PLM, CRM, HRIS, BI, and Big Data platforms.
* Translate business requirements into scalable, standardized, and sustainable technology solutions.
* Lead the design authority function and define global best practices and standards.
* Work closely with the parent company and subsidiaries.
* Own system integrations, data quality, and Data Governance across the application landscape.
* Lead complex technology initiatives end-to-end, from requirements definition through implementation.
* Collaborate closely with cross-functional teams and manage multiple stakeholder interfaces.
* Evaluate and implement new technologies in alignment with organizational strategy.
* Support technology decision-making processes, including Make vs. Buy decisions.
* Define and lead a multi-year application strategy and enterprise roadmap.
* Own the budget, including multi-year planning, financial control, investment prioritization, and ROI management.
* Lead Change Management initiatives, drive standards adoption, and ensure alignment across sites and regions.
* Manage vendors, system integrators, and strategic partners at a managerial level.

DRS RADA is a global pioneer for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance. Role Purpose: Provide executive leadership and strategic direction for the global Applications organization, with full accountability for people, budget, business interfaces, and leading enterprise-wide transformation and organizational change. Key Responsibilities:
* Define and lead a multi-year Applications strategy and an enterprise application roadmap.
* End-to-end accountability for performance, business value delivery, and alignment between technology and business strategy.
* Lead, develop, and manage team leaders and Applications budget management.
* Drive enterprise-level digital transformation and Operational Excellence initiatives.
* Establish governance models, KPIs, and data-driven decision-making processes.
* Manage vendors, system integrators, and strategic partners at the executive level.

our Labs is where innovation meets impact. As the technological powerhouse behind our company, we design and build cutting-edge solutions that revolutionize the insurance industry. Whether its Real-Time claims payments or predictive analytics, our Labs team is at the forefront of driving change and shaping the future of insurance. Ready to innovate with us? We are looking for a FinOps Manager to lead cloud and AI cost optimization, improve financial accountability, and maximize the value of our cloud and AI/ML workloads. This role works across Engineering, DevOps, data, AI/ML, Finance, and Leadership to drive visibility, efficiency, and governance in both cloud infrastructure and AI consumption and will be reporting directly to the VP of IT Infrastructure.
Responsibilities Cloud & AI Cost Optimization
* Own and evolve the organizations FinOps and AIOps cost strategy
* Monitor and optimize spend for:
* Cloud compute, Storage, networking
* SaaS AI services (e.g., OpenAI, Vertex AI, Bedrock, Azure OpenAI)
* Provide actionable recommendations for model selection, right-sizing, and inference optimization. Reporting & Governance
* Build dashboards for Real-Time visibility into cloud and AI cost drivers.
* Implement cost allocation models for training vs. inference, environments, and business units.
* Define tagging standards, budgeting processes, and consumption guardrails.
* Track unit economics such as cost per inference, cost per model training run, and per-product AI usage. Cross-Team Collaboration
* Partner with engineering, data /AI teams, and finance to plan and forecast cloud & AI consumption.
* Guide teams in designing efficient architectures and model deployment strategies
* Educate stakeholders on cost-aware engineering and AI usage best practices.