About Reliance Intelligence
Reliance Intelligence is a Reliance Industries Company building India’s most advanced AI-powered consumer devices. Our flagship product, JioFrames AI, is India’s first AI-powered smart eyewear — combining on-device machine learning, AR overlays, real-time translation, health monitoring, and the JioAI assistant in a sleek wearable form factor. Backed by the JioEcosystem with 450M+ users and unmatched distribution reach, we are building at the intersection of hardware, AI, and consumer experience.
Roles & Responsibilities
- Design, build, and maintain CI/CD pipelines for JioFrames AI software stack — firmware, AI/ML models, Android companion app, and cloud backend services
- Automate build, test, and deployment workflows across development, staging, and production environments
- Manage and scale cloud infrastructure (AWS / GCP / Azure) using Infrastructure as Code (Terraform, Ansible)
- Own containerisation and orchestration — Docker, Kubernetes — for AI inference services and backend microservices
- Implement OTA (over-the-air) update pipelines for JioFrames AI firmware and on-device ML model delivery
- Monitor system health, uptime, and performance using observability tools (Grafana, Prometheus, ELK stack)
- Enforce security best practices — secrets management, access control, vulnerability scanning — across all pipelines
- Collaborate with firmware, AI/ML, and Android teams to streamline release cycles and reduce deployment friction.
Requirements
- 3–6 years of DevOps or Site Reliability Engineering experience
- Strong hands-on experience with CI/CD tools — GitHub Actions, Jenkins, or GitLab CI
- Proficiency with Docker and Kubernetes in production environments
- Experience with cloud platforms — AWS, GCP, or Azure — and IaC tools (Terraform, Ansible)
- Familiarity with OTA update systems for embedded or IoT devices is a strong plus
- Experience with monitoring and observability tools — Prometheus, Grafana, ELK stack
- Scripting skills in Python, Bash, or Go
- Understanding of embedded or wearable device deployment pipelines is advantageous
