Cisco

Claims Specialist

• Manages an inventory of claims to evaluate compensability/liability
• Plans and conducts claim investigations to confirm coverage and to determine liability, compensability and damages
• Determines and negotiates appropriate claim settlements/reserves within prescribed authority
• May attend arbitrations, mediations, depositions, or trials
• Conveys moderately complex information regarding coverage and settlements to insureds, claimants, and external partners
• Authorizes payments in accordance with assigned authority limit and ensures payments are made in a timely manner
• Maintains accurate and detailed claim files, including all correspondence, reports, and settlement agreements
• Performs other duties as assigned.

Senior Claims Representative – Claims Specialist

Artificial Intelligence

• Lead the day-to-day operation of enterprise AI adoption and enablement programs, translating enterprise AI strategy into repeatable execution aligned with enterprise OCM practices.
• Shape program cadence, engagement models, and operating rhythms based on adoption outcomes and evolving AI maturity.
• Plan, organize, and facilitate recurring adoption forums, practitioner communities, and enablement sessions that provide clear agendas, meaningful outcomes, and practical value.
• Serve as the primary point of contact for AI practitioners by providing guidance grounded in AI capabilities and enterprise use cases.
• Track participation, engagement, and early adoption signals to identify risks, misconceptions, and knowledge gaps that require intervention.
• Gather practitioner feedback, recurring questions, and friction points related to AI usage, then synthesize findings into clear themes and recommendations for the Core AI team and leadership.
• Build and maintain AI enablement content and communications, ensuring materials are practical, accessible, aligned to enterprise messaging standards, and kept current over time.
• Communicate adoption progress, risks, and successes clearly to leadership while reinforcing desired behaviors through ongoing cadence, facilitation, and practical examples rather than one-time training efforts.
• Continuously evolve adoption programs to support enterprise needs as AI maturity, tooling, and organizational priorities change.

AI Adoption – Enablement Lead

Operations

• Own and manage the full onboarding lifecycle, ensuring a seamless transition from prospect to active client and a successful hand‑off to Account Management.
• Support agent onboarding, including licensing and appointment coordination.
• Partner with Sales on new business case submissions and track underwriting progress, proactively gathering outstanding requirements.
• Support system automation and process improvements to reduce manual work and increase efficiency.
• Assist agents with Employee Navigator group setup, file testing, and implementation readiness.
• Coordinate with TPAs to ensure accurate and timely case implementation.
• Confirm delivery of required welcome letters and onboarding communications.
• Serve as the primary coordination point during onboarding and the first 30 days post‑implementation.
• Identify and resolve onboarding issues early to minimize disruption and ensure a positive client experience.
• Drive timely, accurate onboarding outcomes, reduced cycle times, improved cross‑functional coordination, and strong client and agent experiences.
• Performs other duties as assigned.

Group Health Insurance Operations Specialist

• Own and maintain the enterprise AI portfolio inventory, including initiatives, status, milestones, dependencies, risks, and outcomes
• Establish and sustain clear traceability from enterprise AI strategy to initiatives and delivered business value
• Design, build, and maintain executive dashboards and portfolio reporting views used for leadership decision-making
• Define and manage portfolio KPIs and metrics, including value delivered, adoption, delivery health, risk, capacity, duplication, and maturity
• Deliver fact-based insights that support prioritization, sequencing, capacity planning, and leadership trade-off decisions
• Identify and surface portfolio risks early, including over-commitment, duplication, stalled initiatives, misalignment to strategy, and unclear outcomes
• Develop and maintain a lightweight governance model that aligns teams and supports consistent portfolio reporting without unnecessary bureaucracy
• Establish and lead a portfolio operating cadence, including monthly portfolio reviews and quarterly strategy and value refreshes
• Drive portfolio hygiene and continuous improvement by ensuring timely updates, addressing aging or stalled work, and reducing manual reporting effort

Enterprise AI Portfolio Manager

Security Engineer

• Identify and focus on threat research and insider risk
• Conduct threat hunting using logs, telemetry, and behavioral indicators across endpoints
• Produce clear, defensible investigative reports
• Support ELT incident response and mitigate critical IP theft
• Draft and document internal solutions responsive to emerging insider risks
• Conduct and document hands-on technical research on potential digital threats

Threat Intelligence Investigator – Global Security & Executive Protection

Data Engineer

• Architect and maintain robust, scalable data ecosystems that transform raw information into actionable business intelligence.
• Serve as a technical bridge between complex data infrastructure and cross-functional stakeholders.
• Architect and optimize high-throughput ETL/ELT pipelines.
• Design and manage enterprise-grade data warehouses and lakes.
• Enforce rigorous data quality standards and security protocols.
• Collaborate with data scientists and business analysts to translate complex requirements into high-performance data models.
• Identify and automate manual data workflows.

Software Engineer

• Design, develop, and manage AI-driven observability products or product portfolios that provide end-to-end visibility, monitoring, and assurance for sophisticated applications and infrastructure.
• Take end-to-end ownership of multiple observability products within a portfolio, driving innovation in AI-powered monitoring, troubleshooting, remediation, and incident response.
• Shape the product portfolio strategy over a 12-18 month horizon, with clear milestones focused on enhancing observability capabilities such as AI-driven root cause analysis, anomaly detection, alert correlation, and remediation.
• Develop multi-quarter product roadmaps that align market needs, AI observability trends, AI evaluation quality standards, and business strategy.
• Provide input into competitive analysis and market validation for AI observability.
• Solicit and incorporate customer feedback from diverse channels to continuously improve observability features, AI evaluation quality, and user experience.
• Create alignment between product teams, stakeholders, and leadership to strengthen AI observability product lines and drive adoption.
• Act as a product spokesperson internally and externally, evangelizing observability innovations, and benefits.

Engineering Product Manager – Observability AI

Engineer

• Implementing Hardware Design-for-Test (DFT) features supporting ATE, in-system test, debug and diagnostics
• Development of innovative DFT IP in collaboration with multi-functional teams
• Key role in full chip design integration with testability features
• Work closely with design/design-verification and PD teams for test logic integration
• Enable validation of Test logic in all phases of implementation and post-silicon validation flows

ASIC DFT Engineer, DFT/ATPG/MBIST/SCAN/JTAG

Full-stack Engineer

• Develop high-quality, secure software solutions that simplify complex legal processes to enhance the productivity of Cisco’s Legal & Compliance teams.
• Partner with cross-functional teams, including design and product management, to translate user requirements into intuitive, user-friendly applications.
• Apply secure coding principles to ensure the integrity and privacy of sensitive legal data across all systems.
• Contribute to the full software development lifecycle, from initial design and coding to unit testing and production support, to ensure reliable and scalable performance.
• Experiment with emerging technologies like Generative AI to automate routine tasks and drive innovation in our existing software ecosystem.

• develop and execute sales strategies and tactics
• responsible for accurate forecasting and regular deal reviews
• lead account executives in development and expansion of opportunities
• engage in deal inspection and drive accountability
• build and maintain strong executive-level relationships

Regional Sales Leader – Security

SDET

• Play a pivotal role in advancing Cisco’s cutting-edge ASIC technology.
• Lead the ATE test bring-up process.
• Collaborate with talented teams to develop, refine, and release test programs for production.
• Drive pattern generation, troubleshooting, and test coverage optimization.
• Design and implement innovative tests and proactively identify and close coverage gaps.
• Manage manufacturing test operations and tackle quality challenges alongside Tier-1 OSATs.

ASIC Hardware Test Engineer

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Software Engineer Full Stack – Application Development

Sales Engineer

• gain insight into how Cisco’s technical sales teams help customers solve complex business challenges with technology
• demonstrate how AI-enabled tools and research techniques help technical sellers understand customer environments, identify use cases, and plan solution strategies that improve seller productivity
• learn how Solutions Engineers position Cisco’s portfolio across areas such as AI infrastructure, security, networking, collaboration, and cloud while understanding competitive differentiation
• build foundational skills in technical demos, whiteboarding, and solution storytelling used to communicate complex technologies
• observe customer discussions, product demonstrations, and internal technical strategy sessions
• gain exposure to how technical sellers guide opportunities through technical validation and technical close
• deliver presentations to account teams and sales leaders, sharing insights and recommendations from your research and project work.

Technical Sales Engineer Intern

• Participate in developing advanced data pipelines, machine learning infrastructure, and analytics platforms.
• Contribute to the growth of emerging technologies in data and intelligent systems.
• Solve complex challenges with innovation and attention to detail.
• Build and maintain key software tools and platforms to leverage AI and data-driven insights.

Software Engineer – Data, AI, Intelligent Systems

• work directly with your Manager and Mentor to gain hands on experience of developing software solutions
• participate in day-to-day delivery activities such as coding, customer meetings, deliverable creation, building labs, DevOps, deployment, and troubleshooting
• leverage your coursework and experience in real-world scenarios as a full stack developer
• likely gather experience in Java, Gradle, Spring, Python, Ansible