Meet the Team The Collaboration Technology Group is redefining the future of teamwork, building services that connect people effortlessly across devices, locations and time zones.
Our team in Stockholm builds, runs, and continuously improves the core media platform services behind Cisco’s collaboration products, operating at global scale across numerous datacentres.
We’re a passionate, collaborative team focused on real-time media reliability, innovation, and engineering excellence.
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.
Responsibilities
As a Software Engineer in our Stockholm Webex Media (WxMedia) & SRE organization, you will bring new real-time media features to life and drive resolution for high-impact media platform escalations.
You will combine
Site Reliability Engineering practices with real-time media streaming architectures and modern agentic AI (reusable Skills, Model Context Protocol (MCP), and LLM tooling) to transform how we monitor, diagnose, and auto-remediate global media services handling billions of audio and video minutes.
Media Escalations & Real-Time Reliability: Deep-dive troubleshooting for complex WxMedia platform issues, investigating packet loss, jitter, latency, audio/video degradation, and SIP/WebRTC signalling failures across hybrid cloud and bare-metal environments.
Design and implement high-resilience software systems for AI-assisted observability, automated incident response, and self-healing cloud media 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 meticulous safety, security, and quality guardrails.
Partner with application and infrastructure teams to define SLIs/SLOs, handle error budgets, and lead investigation post-incident reviews (PIRs).
Mentor junior engineers, conduct thorough code reviews, establish engineering standards, and drive operational excellence across global development and operations teams.
Manage priorities and timelines, 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 with media streaming or relevant protocols for real-time applications (e.g., RTP/RTCP, SRTP, WebRTC, SIP, SDP, RTSP, or HLS/DASH).
Experience in some of SRE practices (e.g. SLI/SLO design, observability platforms (metrics/logs/traces), incident management, and automated root cause analysis (RCA)) Preferred Qualifications Experience with public cloud platforms (AWS, Microsoft Azure, or Google Cloud).
Experience with close-to-real-time systems and performance-sensitive code paths.
Comfort with incremental development, testing, and A/B testing in production.
Steers AI effectively via context and prompt design.
Experience building LLM pipelines, AI Agents, Model Context Protocol (MCP) servers/clients, RAG architectures, and evaluation frameworks.
Experience with OpenTelemetry (OTel), Prometheus, Grafana, Splunk, ThousandEyes, or distributed tracing systems.
Expertise in Terraform/IaC and GitOps/CI/CD pipelines (Jenkins, GitHub Actions, Harness).
Experience implementing responsible AI guardrails, deterministic fallback logic, and policy-driven remediation engines.
Experience with streaming and data platforms (Kafka, Redis, PostgreSQL, Elasticsearch/Vector DBs).
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