Software Engineer (Senior / Tech Lead level)

In Cisco Enterprise AI Platforms & Infrastructure (EAIPI), our vision is to architect, build, and scale world-class agentic AI platforms, foundation infrastructure, and developer ecosystems that power Cisco's next generation of intelligent products and services.

As a Software Engineer (Senior / Tech Lead level) in Cisco EAIPI, you will serve as an advanced technical professional driving end-to-end software engineering excellence across our flagship AI platforms. Developing software consistent with Cisco ‘Design Thinking Principles’, you will place simplification and User Experience (UX) at the core while upholding strict secure coding standards, user privacy, and engineering best practices.

Responsibilities:

• Apply advanced proven experience, industry procedures, and deep systems understanding to solve technical problems and elevate product capabilities.
• Work with high autonomy and minimal guidance, resolving optimal architectural patterns, technical designs, and implementation approaches.
• Drive initiatives from end-to-end by scoping requirements, delegating tasks, conducting technical reviews, and delivering well-rounded results on schedule.
• Lead medium-to-large feature delivery from architectural design through testing, deployment, and post-launch optimization.
• Write clean, high-performance, and modular code along with comprehensive test suites without requiring guidance.
• Conduct deep, meticulous code reviews to identify both immediate bugs and broader architectural risks, maintaining an extraordinarily high quality bar.
• Test, profile, and optimize code to enhance scalability, execution velocity, token throughput, and runtime reliability across distributed systems.
• Supply directly to threat modeling, secure architecture design, and data privacy safeguards across all platform features.
• Monitor production health, serve as a customer concern point for on-call issues, lead blameless postmortems, and author comprehensive Root Cause Analysis (RCA) reports.
• Serve as a recognized Domain Authority (SME) across multiple core functional components and AI platform subsystems.
• Build strong multi-functional partnerships across Product Management, Design, SRE, and Security to identify multi-product harmonies and customer value.
• Track product adoption, performance metrics, and competitive landscapes, integrating market insights directly into technical feature designs.
• Coordinate across engineering teams to provide accurate estimations, achievement tracking, and proactive risk remediation plans.
• Share technical knowledge proactively through internal blogs, tech talks, architecture RFCs, and engineering newsletters.
• Mentor peer engineers and junior team members, elevating the overall engineering density through technical guidance and pair programming.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related STEM field + 7 years of related experience; OR Master’s degree + 4 years of related experience; OR Ph.D. + 1 year of related experience.
• Solid conceptual and practical expertise in software engineering and distributed systems, with broad proficiency across multiple technical job families and modern technology stacks.
• Expert-level hands-on coding proficiency in one or more core languages (Python, TypeScript/JavaScript, Go, Java, C++, or Rust) with confirmed experience architecting and shipping critically important, enterprise-grade software.
• Consistent track record of independently leading complex technical features, driving architectural design RFCs, and applying agile engineering standard methodologies across the full SDLC.
• Strong background in writing modular, highly testable code, designing automated test suites, and performing comprehensive code reviews.

Preferred Qualifications:

• Hands-on production experience with Generative AI technologies, LLMs, Model Context Protocol (MCP), LangGraph, LlamaIndex, vLLM, or multi-agent orchestration frameworks.
• Experience architecting and scaling high-concurrency microservices, low-latency APIs, event-driven architectures (Kafka, RabbitMQ), and distributed caching (Redis).
• Deep familiarity with cloud-native infrastructure, container orchestration (Docker, Kubernetes), GPU compute environments (Triton Inference Server, CUDA), and vector databases.
• Expertise in enterprise security patterns, OAuth 2.0 / Token Exchange (RFC 8693), Zero Trust architecture, and automated threat modeling.
• Hands-on experience with modern observability stacks (OpenTelemetry, Prometheus, Splunk, Grafana) and automated CI/CD deployment pipelines (Canary/Blue-Green deployments).
• Exceptional communication, presentation, and multi-functional leadership skills with the ability to influence technical roadmaps and mentor engineering teams.