Job Description – Production Deployment Engineer
Company: CogniAI Advanced Research Solutions Pvt. Ltd.
Position: Production Deployment Engineer
Location: Perungudi, Chennai (Work from Office)
Department: Engineering / DevOps
Employment Type: Full-Time
Experience: 4+ Years
About CogniAI
CogniAI Advanced Research Solutions Pvt. Ltd. is an AI-first technology company delivering innovative solutions across Healthcare, Government, Enterprise Automation, and Civil Engineering. Our products leverage Artificial Intelligence, Cloud Computing, and Automation to build scalable, secure, and intelligent enterprise platforms.
We are looking for a highly skilled Production Deployment Engineer to own the reliability, scalability, and efficiency of our software deployment process. This role bridges software engineering and cloud infrastructure, ensuring applications move seamlessly from development to production while maintaining high availability, security, and performance.
Position Summary
As a Production Deployment Engineer, you will be responsible for designing and managing deployment pipelines, container orchestration, cloud infrastructure, and production environments. You will work closely with software engineers, AI engineers, QA teams, and product managers to ensure reliable, automated, and secure software releases.
Key Responsibilities
- Design, build, and maintain scalable CI/CD pipelines for automated application deployments.
- Manage containerized applications using Docker and orchestrate workloads using Kubernetes.
- Implement deployment strategies such as Blue-Green, Canary, and Rolling Deployments to minimize production risk.
- Automate infrastructure provisioning using Infrastructure-as-Code tools such as Terraform, Helm, or similar.
- Collaborate with development teams to ensure applications are production-ready, scalable, secure, and observable.
- Monitor production environments using modern observability tools and define service reliability metrics (SLIs/SLOs).
- Improve deployment speed, system reliability, and operational efficiency while reducing deployment failures.
- Implement automated testing, security scanning, vulnerability management, and rollback mechanisms within deployment pipelines.
- Troubleshoot production issues, perform root cause analysis, and participate in incident response and post-incident reviews.
- Configure monitoring, logging, alerting, and performance dashboards for production systems.
- Maintain deployment documentation, runbooks, disaster recovery plans, and operational procedures.
- Ensure production environments follow security, compliance, and best DevOps practices.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 4+ years of experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, or Production Deployment.
- Strong hands-on expertise with Docker, including image optimization, multi-stage builds, image security, and registry management.
- Extensive experience with Kubernetes, including Deployments, Services, Ingress Controllers, RBAC, ConfigMaps, Secrets, Persistent Storage, Autoscaling (HPA/VPA), and cluster troubleshooting.
- Experience building CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, ArgoCD, Azure DevOps, or similar tools.
- Proficiency in at least one programming or scripting language such as Python, Go, Node.js, Java, or Bash.
- Hands-on experience with AWS, Microsoft Azure, or Google Cloud Platform.
- Experience with Infrastructure-as-Code tools such as Terraform, Helm, Pulumi, or CloudFormation.
- Strong understanding of networking concepts including DNS, Load Balancers, TLS/SSL, Reverse Proxies, Firewalls, and Secrets Management.
- Experience with monitoring and observability tools such as Prometheus, Grafana, ELK Stack, Datadog, or OpenTelemetry.
- Strong Linux administration and troubleshooting skills.
Preferred Qualifications
- Certified Kubernetes Administrator (CKA) or equivalent certification.
- Experience implementing GitOps workflows using ArgoCD or Flux.
- Knowledge of service mesh technologies such as Istio or Linkerd.
- Experience supporting AI/ML platforms or cloud-native microservices.
- Familiarity with database migration strategies and zero-downtime deployments.
- Experience managing high-availability, mission-critical production environments.
- Contributions to open-source DevOps, Kubernetes, or cloud-native projects.
Technical Skills
- Docker
- Kubernetes
- Helm
- Terraform
- GitHub Actions
- GitLab CI/CD
- Jenkins
- ArgoCD
- Azure DevOps
- AWS / Azure / GCP
- Linux
- Bash
- Python
- Go
- Prometheus
- Grafana
- ELK Stack
- OpenTelemetry
- NGINX
- Git
Why Join CogniAI?
- Work on cutting-edge AI and cloud-native enterprise platforms.
- Build and manage scalable Kubernetes-based production environments.
- Collaborate with AI engineers, software developers, and cloud architects.
- Opportunity to implement modern DevOps, GitOps, and automation practices.
- Competitive salary, continuous learning opportunities, and career growth in a fast-growing AI company.
Pay: ₹30,000.00 - ₹70,000.00 per month
Benefits:
- Health insurance
- Provident Fund
Work Location: In person
