• Own the architecture of the vehicle and phone onboarding flows • Review and approve all pull requests for your squad • Drive sprint planning with the Product Owner • Unblock engineers actively • Model AI-native engineering

• Be at the forefront of IFS product implementations working directly with customers and partners • Take the lead in delivering the IFS solution, maintain clear communication on all aspects of the solution • Work closely with the IFS Project Manager to ensure risks from complex requirements are minimized • Coordinate and delegate work within the delivery team • Work with partners and system integrators to ensure the IFS experience is consistent • Advise on the successful application of IFS Accelerators • Focus on ensuring delivery of value to the customer • Be involved in the successful delivery of additional consulting services

• Inspire and mentor a high-performing team, fostering a culture of continuous improvement and technical excellence. • Develop talent, set clear expectations, and ensure team consistently delivers innovative solutions that align with Cisco’s strategic vision. • Champion a customer-centric mindset, leading your team to meet and exceed revenue and operational targets. • Serve as a mentor, guiding engineers through career development while cultivating a robust technical community. • Act as a strategic advisor to customers and partners, cultivating executive-level relationships that drive long-term loyalty and transformative security outcomes. • Proactively monitor industry trends, particularly the rapid evolution of AI, guiding the team in crafting innovative solutions. • Standardize technical sales methodologies and assets, demonstrating the value of Cisco Security solutions, driving growth.

Role Description Translating AI capabilities into business value requires a technically versatile engineer who can bridge the gap between complex AI models and practical applications. This implementation-oriented full-stack role combines software engineering expertise with specialized knowledge of how to efficiently leverage data sources, LLMs, and AI agents in production environments to deliver tangible business value. - Accelerates user adoption through intuitive interfaces and seamless system integrations - Creates efficient data pipelines connecting LLMs to relevant utility information sources - Enables intelligent automation through multi-agent systems for complex workflows - Develops sustainable solutions that can evolve with business needs and technology advances - Build proof-of-concept applications and production-ready interfaces for GenAI capabilities - Connect AI services with enterprise systems (SAP, internal databases) for data exchange - Design and implement multi-agent architectures to solve complex business processes - Develop tool integration frameworks allowing AI to interact with utility systems - Create robust memory and reasoning systems for contextual, multi-step AI interactions - Implement appropriate guardrails and safety measures for AI agent systems - Gather requirements and translate business needs into technical implementation - Produce documentation and knowledge transfer materials for sustainable solutions Qualifications - Full-Stack Development: Modern front-end frameworks, back-end technologies, API design - System Integration: Experience connecting disparate systems, data orchestration, authentication - AI Application Patterns: RAG architectures, prompt engineering, agent orchestration frameworks - Agent Architecture: Knowledge of multi-agent systems, collaboration protocols, tool integration - Reasoning & Memory: Understanding of chain-of-thought reasoning, context management, planning algorithms - User Experience: Ability to design intuitive AI interfaces with appropriate feedback mechanisms - Rapid Prototyping: Demonstrated ability to quickly build working demos and iterate based on feedback Company Description