Platform Engineer — Core Infrastructure

Team: DevOps Team

Location: Bengaluru

Commitment: Full Time

Workplace Type: onsite

What Will You Do

• Own and operate production infrastructure across multiple GKE clusters supporting both real-time video workloads and AI agent pipelines — with HA, autoscaling, and full observability tuned to the demands of each.

• Manage GitOps workflows using Argo CD for automated, version-controlled, and auditable deployments across both product lines.

• Maintain and optimize monitoring & alerting stacks using Open Source Monitoring Tools — with product-specific SLOs for low-latency video (jitter, packet loss, stream health) and AI workflow reliability (task throughput, failure rates, retry queues).

• Implement infrastructure as code using Terraform for GCP resources and helm chart for Kubernetes manifests, with a strong bias toward repeatability and auditability.

• Support the unique infrastructure demands of real-time video — including media server scaling, WebRTC infrastructure, low-latency networking, and high-throughput data paths.

• Support AI agent workloads — including LLM inference infrastructure, async task queues, and integration pipelines with external healthcare systems.

• Lead or support incident response, cluster upgrades, and disaster recovery procedures across both platforms.

• Own the security posture of our infrastructure — enforce least-privilege access controls, manage secrets hygiene, and drive security hardening across clusters and services.

• Implement and maintain compliance-aligned controls relevant to healthcare data environments (e.g., encryption at rest/in transit, audit logging, network segmentation).

• Collaborate with product and engineering teams to embed security early in the development lifecycle — shift-left on vulnerability scanning, dependency audits, and policy enforcement.

Who Can Apply

 

• Computer Science / Engineering degree or equivalent practical experience.

• Minimum 3 years of hands-on experience with Kubernetes in a production environment.

• Strong knowledge of CI/CD pipelines and GitOps workflows using Argo CD or similar tools.

• Proficient in infrastructure automation using Terraform and Helm.

• Experience in managing open source monitoring and logging stacks (Prometheus, Loki, Grafana, Alertmanager etc).

• Working knowledge of cloud security principles — IAM, network policies, pod security, RBAC, and secrets management.

• Comfortable with Linux systems, shell scripting, and basic networking — including an understanding of UDP/TCP behaviour relevant to real-time media or distributed systems.

Good to Have

• Prior experience managing large-scale, multi-tenant or mixed-workload infrastructure.

• Exposure to real-time media infrastructure — WebRTC, SFUs, TURN/STUN servers, or media server orchestration.

• Hands-on experience with secrets management tools such as HashiCorp Vault or Sealed Secrets.

• Familiarity with security scanning and policy tools (e.g., Trivy, OPA/Gatekeeper, Falco).

• Experience with GCP and GKE specifically.

• Exposure to compliance frameworks relevant to healthcare or regulated industries (HIPAA awareness is a plus).

• Experience with AI/ML inference workloads or async pipeline infrastructure (queues, workers, orchestrators).

• Experience with open source contributions.

• Strong inclination to stay current with evolving infrastructure, security, and platform engineering practices — and a willingness to share ideas internally or externally.

• Ability to communicate fluently and clearly in English, written and spoken.

Why 100ms

• You'll work on genuinely varied infrastructure — real-time video at scale and AI-driven healthcare automation are both hard problems with different constraints, and you'll own both.

• You'll be part of a small, high-ownership team at a fast-growing, engineering-first startup with a meaningful mission — powering real-time experiences and helping patients access treatment faster.

• You'll work alongside engineers with deep experience in distributed systems, real-time media, AI infrastructure, and platform engineering at scale.

• You'll have the freedom to grow as an individual contributor or step into a team leadership role — with room to define your own goals and impact.

• Security and infrastructure are first-class concerns here, not support functions — your work directly shapes the trust and reliability our customers depend on.

Additional Information

• We place a strong emphasis on in-office collaboration to maintain a tight feedback loop and a strong engineering culture.

• Employees are expected to work from the office at least three days a week.

Website

https://www.100ms.ai/
https://www.100ms.live