Senior Software Engineer

Forward Deployed Software Engineering (FDSE) at Cisco builds production-grade software integrating Splunk and Cisco technologies, working closely with customers and cross-functional teams to solve complex problems and deliver scalable, reusable solutions globally.

• Bachelor's or master's degree in computer science, Software Engineering, or related technical field (or equivalent experience)
• 6+ years of professional experience designing, developing, and delivering production-grade software applications
• Experience developing software using modern programming languages, with a preference for Python
• Experience building applications, integrations, APIs, or cloud-native services
• Experience with enterprise platforms, distributed systems, cloud technologies, or automation frameworks
• Experience using modern AI development tools and APIs as part of the software engineering lifecycle

Preferred Qualifications:

• Experience with Splunk, including application, dashboard, data integration, or operational workflow development
• Experience building AI-enabled applications using LLMs, RAG, vector databases, AI agents, Model Context Protocol (MCP), or similar technologies
• Experience developing cloud-native applications using AWS, Azure, GCP, or similar platforms, including Infrastructure as Code and CI/CD practices
• Experience in customer-facing engineering organizations such as Forward Deployed Engineering, Solutions Engineering, Professional Services, or Technical Consulting
• Excellent communication, presentation, and stakeholder management skills, able to explain technical concepts to technical and non-technical audiences

• Design, develop, and deliver production-grade software solutions addressing complex operational challenges
• Lead technical initiatives from discovery to production, making architectural decisions balancing rapid delivery and maintainability
• Partner with customers, Solution Engineers, Product Engineering, and Customer Experience teams to understand problems and deliver measurable value
• Build modern integrations, automation, AI-enabled capabilities, and cloud-native applications by rapidly learning new technologies
• Provide technical leadership through architecture discussions, mentoring, code reviews, and engineering best practices
• Evolve reusable frameworks, engineering standards, and open-source solutions
• Leverage AI-assisted engineering tools like Claude Code and Codex to accelerate software development while maintaining quality, security, and production readiness
• Design and deliver AI-powered capabilities and application patterns where appropriate