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About the Role
As a Software Engineer, you will design, build, and deploy the core capabilities of our next-generation AI-powered Production Intelligence platform. You will combine Site Reliability Engineering practices with modern agentic AI to transform how engineering and leadership teams monitor, diagnose, and auto-remediate global SaaS infrastructure.
Responsibilities
- Design and implement high-resilience software systems for AI-assisted observability, automated incident response, and self-healing cloud infrastructure.
- Design, build, and maintain production-grade AI agents, MCP tool integrations, and deterministic evaluation pipelines for automated operational decision support.
- Implement ingestion and correlation pipelines across distributed logs, metrics, OpenTelemetry traces, change events, and runbooks to accelerate Mean Time to Detection (MTTD) and Resolution (MTTR).
- Develop proactive anomaly detection and Human-in-the-Loop (HITL) remediation workflows with rigorous safety, security, and quality guardrails.
- Partner with application and infrastructure teams to define SLIs/SLOs, handle error budgets, and lead deep-dive post-incident reviews (PIRs).
- Mentor mid-level and junior engineers, conduct thorough code reviews, establish engineering guidelines, and drive operational excellence across global development and operations teams.
- Manage priorities and deadlines, communicate progress clearly, and work across teams to turn production needs into reliable software and AI-assisted capabilities.
Requirements
- Bachelor’s degree + 8 years of related experience, Master’s + 6 years, or PhD + 3 years in Computer Science, Software Engineering, or a related technical field.
- Experience as a Senior / Lead SRE or Software Engineer delivering distributed, high-availability SaaS platforms at scale.
- Strong proficiency in Python, Go, Java, or C++ with experience designing microservices, APIs, and production automation.
- Deep experience with Kubernetes, Docker, and container orchestration in large-scale multi-cluster environments.
- Proven background in SRE practices: SLI/SLO design, observability platforms (metrics/logs/traces), incident management, and automated root cause analysis (RCA).
Skills
- AI Agents
- Model Context Protocol (MCP)
- LLM tooling
- Python
- Go
- Java
- C++
- Microservices
- APIs
- Production automation
- Kubernetes
- Docker
- Container orchestration
- SLI/SLO design
- Observability platforms
- Incident management
- Automated root cause analysis (RCA)
- LLM pipelines
- RAG architectures
- Evaluation frameworks
- OpenTelemetry (OTel)
- Prometheus
- Grafana
- Splunk
- ThousandEyes
- Distributed tracing systems
- Public cloud providers (AWS, GCP, Azure)
- Terraform/IaC
- GitOps/CI/CD pipelines
- Jenkins
- GitHub Actions
- Harness
- Responsible AI guardrails
- Deterministic fallback logic
- Policy-driven remediation engines
- Streaming and data platforms
- Kafka
- Redis
- PostgreSQL
- Elasticsearch/Vector DBs
Experience Level
- Senior / Lead SRE
- Software Engineer
Education Level
- Bachelor’s degree
- Master’s degree
- PhD
About the Company
- At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond.
- We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds.
- These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
- Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions.
- Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless.
- We work as a team, collaborating with empathy to make really big things happen on a global scale.
- Because our solutions are everywhere, our impact is everywhere.
- We are Cisco, and our power starts with you.