• Work closely with engineering, product, and architecture teams • Review current AI initiatives with engineering teams • Design reference architecture for multi-agent orchestration • Collaborate on context management strategy • Design RAG architecture with data and ML teams • Establish prompt governance practices • Define platform resiliency patterns for LLM-dependent systems • Set AI safety and governance standards • Partner with leadership to build implementation roadmap

• Partner with Account Executives to drive business and growth opportunities. • Driving demand generation activities. • Enable technology capabilities internally with Portfolio Account Teams and externally with our partners. • Understanding customer requirements and mapping technical solutions to meet the needs. • Network design. • Performing product demo and Proof of Concept (PoC) labs. • Maintaining competitive knowledge to strategically position Cisco’s products and services. • Following market transition and industry trends to anticipate customer needs. • Aligning cross-functionally to various business entities and teams across the company.

• Act as a trusted advisor to clients, prospects and partners, engaging at senior levels to quickly understand their technology ecosystems, operational challenges, and business goals. • Collaborate with clients and vendors on innovative solutions that integrate WideOrbit’s products with third-party tools, data sources, and workflows. • Lead discovery engagements to identify business objectives, operational challenges, technical requirements, and success criteria. • Develop consensus with clients on quantifiable success metrics for each engagement, ensuring that WideOrbit’s internal measures of value align with the clients. • Occasionally lead or support client-facing demonstrations, translating complex technical capabilities into clear, business-focused value. • Develop solutions and workflows tailored to meet unique client business objectives, either fully contained within the WideOrbit ecosystem or as part of a larger, integrated stack. • Map client’s existing business processes, workflows, and associated costs, identifying high leverage opportunities and prioritizing those in project planning. • Provide technical guidance, subject matter expertise, and product knowledge during sales engagements supporting complex deal negotiations and renewals. • Orchestrate the solution implementation process, ensuring smooth adoption, addressing technical and operational gaps, all while architecting the next phase of the solution. • Work closely with Sales, Product, Engineering, and Professional Services teams to align client priorities, market demands, and growth strategies. • Collaborate on strategies to enhance client satisfaction, identify revenue opportunities, and ensure successful long-term partnerships. • Maintain expertise in media, advertising technology, and operational workflows to ensure solutions meet industry challenges and trends. • Identify opportunities for product enhancements or integrations, advocating for innovation based on client feedback and market needs. • Partner with internal teams to evolve WideOrbit’s offerings, maintaining a leadership position in the ad tech ecosystem.

• Lead discovery with business and technology partners to understand objectives, constraints, current-state systems, and integration points. • Document current-state architecture and define target-state designs including system context diagrams, component designs, integration patterns, and data flows. • Design and modernize applications into cloud-compatible or cloud-native architectures using microservices, serverless, and event-driven patterns where appropriate. • Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms. • Design AI and ML-enabled solutions, including model integration into products and business processes, and patterns for scalable inference and low-latency serving where needed. • Design Generative AI solution patterns, such as retrieval-augmented generation, tool and API integration, prompt and context management, and evaluation approaches. • Define reference architectures for AI platforms and enabling capabilities, such as data pipelines, feature and embedding generation, vector storage, model endpoints, and integration with enterprise APIs. • Establish best practices for MLOps and AI operations, including model versioning, deployment, monitoring, drift detection, incident response, and cost management. • Incorporate security-by-design practices into architectures, including identity and access controls, encryption, secrets management, secure networking, and audit logging. • Partner with governance and risk stakeholders to ensure responsible AI considerations are incorporated, including privacy, explainability, safety, compliance, and model risk controls as applicable. • Drive alignment and adoption of proposed solutions by clearly communicating tradeoffs, risks, and value and obtaining stakeholder alignment and governance approvals. • Support teams responsible for testing and validation and help triage and resolve design-related issues found during development, UAT, or production. • Perform other duties as assigned.