Senior DevOps Engineer | AI-Driven Tech Startup
Location : Hyderabad (Hybrid)
Experience : 8+ years
Type : Full-time
About Ekshvaku Tech Innovations
Ekshvaku Tech Innovations is a fast-growing AI-driven technology company redefining how clinicians and healthcare systems harness data for better decision-making. Our mission is to build secure, intelligent, and scalable AI solutions that empower healthcare professionals to improve patient outcomes and operational efficiency.
Join a passionate and dynamic team where your expertise in automation, scalability, and cloud infrastructure will directly fuel life-changing innovations in healthcare technology.
What You’ll Do
As a Senior DevOps Engineer, you will lead the design, automation, and management of our AI and data infrastructure. You’ll drive DevOps excellence across CI / CD, cloud, observability, and security — ensuring that our systems are fast, reliable, and compliant with healthcare standards.
Key Responsibilities :
- Design, implement, and maintain CI / CD pipelines across QA, staging, and production.
- Automate infrastructure provisioning and configuration using Terraform, Ansible, or CloudFormation.
- Deploy and manage AI / ML workloads on AWS or GCP.
- Lead containerization and orchestration using Docker and Kubernetes (EKS / GKE).
- Implement end-to-end monitoring, logging, and alerting for proactive system health management.
- Ensure HIPAA compliance, robust security, and effective disaster recovery strategies.
- Collaborate closely with AI, Data, and Software Engineering teams to streamline model deployment workflows.
- Explore and integrate AI-assisted DevOps tools for automation and observability.
What You Bring
8+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering.Proven expertise with CI / CD tools (GitHub Actions, Jenkins, etc.).Strong proficiency in AWS or GCP (IAM, networking, autoscaling, etc.).Hands-on experience with Docker & Kubernetes (EKS, GKE).Strong scripting skills in Python, Bash, or Go.Experience with Infrastructure as Code (Terraform, CloudFormation, Ansible).Familiarity with ML Ops tools (MLflow, Kubeflow, Vertex AI, SageMaker).Deep understanding of monitoring & observability stacks (Prometheus, Grafana, ELK).Knowledge of security practices, zero-trust architecture, and compliance frameworks.Strong communication and documentation skills for effective cross-team collaboration.Mandatory Skills
Experience with GPU orchestration or AI / ML model pipeline automation.Exposure to serverless / event-driven architectures (AWS Lambda, Cloud Run).Hands-on with GitOps tools (Argo CD, Flux).AWS DevOps Engineer – Professional certification or equivalent.Background in healthcare or other regulated data environments.Impact & Success
90%+ reduction in manual deployments via automation.Faster and more reliable release cycles.Enhanced observability and proactive system monitoring.Modernized infrastructure supporting next-gen AI healthcare workloads.