Job Description – Computing Specialist

Position: Computing Specialist
Department: Technology / R&D;
Location: Cuttack, Bhubaneswar
Employment Type: Full-Time
Experience: 2–3 Years
Reporting To: CTO / Technical Lead

About the Role

We are looking for a Computing Specialist to design, deploy, maintain, and optimize computing infrastructure supporting our software, IoT, automation, AI/ML, and data-driven technology platforms.

The candidate will be responsible for managing computing environments across on-premise servers, cloud infrastructure, edge devices, and development systems, ensuring high availability, performance, security, and scalability.

Key Responsibilities

1. Computing Infrastructure

- Configure, deploy, and maintain Linux and Windows-based servers and computing systems.
- Manage CPU, GPU, RAM, storage, networking, and other computing resources.
- Monitor system performance, resource utilization, uptime, and capacity.
- Perform system optimization, troubleshooting, upgrades, and preventive maintenance.
- Maintain computing environments for R&D;, production, and field deployments.

2. Cloud & Server Management

- Deploy and manage applications and services on cloud and on-premise infrastructure.
- Work with platforms such as AWS, Azure, Google Cloud, or equivalent.
- Configure virtual machines, containers, storage, networking, and access controls.
- Support server-level deployment of web and mobile application backends.
- Implement backup, disaster recovery, and system restoration procedures.

3. Edge Computing & IoT

- Configure and maintain edge computing systems deployed at project/customer sites.
- Support Raspberry Pi, NVIDIA Jetson, industrial PCs, gateways, and similar platforms.
- Enable reliable communication between sensors, controllers, edge devices, and cloud platforms.
- Troubleshoot connectivity, compute, storage, and deployment issues in field environments.

4. DevOps & Deployment

- Develop and maintain CI/CD pipelines for software deployment.
- Use Docker and container-based deployment practices.
- Automate system provisioning, deployment, monitoring, and routine administration.
- Maintain Git-based development and release workflows.
- Support version control, rollback, release management, and environment configuration.

5. AI/ML & High-Performance Computing

- Support GPU-enabled computing environments for AI/ML workloads.
- Configure CUDA/GPU environments where required.
- Optimize computing resources for data processing, computer vision, analytics, and machine-learning applications.
- Support deployment of AI/ML models on cloud and edge devices.

6. System Monitoring & Security

- Implement system monitoring, logging, alerting, and performance dashboards.




- Identify and resolve system failures, bottlenecks, and security vulnerabilities.
- Manage user accounts, permissions, SSH access, firewall rules, and system security.
- Follow appropriate cybersecurity and data-protection practices.
- Maintain documentation of infrastructure configurations and dependencies.

7. Technical Support & Troubleshooting

- Provide technical support to software, embedded, IoT, and R&D; teams.
- Diagnose hardware, OS, networking, deployment, and application-level infrastructure issues.
- Support remote troubleshooting of systems deployed at customer/project locations.
- Coordinate with hardware and software teams for integrated system debugging.

8. Documentation

- Maintain detailed documentation of:
- Server configurations
- Network architecture
- Deployment procedures
- Cloud infrastructure
- Software environments
- Credentials/access procedures
- Backup and recovery processes
- Troubleshooting procedures
- Prepare standard operating procedures (SOPs) to ensure continuity when team members change.

Required Technical Skills

- Strong knowledge of Linux system administration.
- Working knowledge of Windows Server environments.
- Knowledge of networking: TCP/IP, DNS, DHCP, VPN, SSH, HTTP/HTTPS, firewalls.
- Experience with Docker and containerized applications.
- Familiarity with Git/GitHub/GitLab.
- Experience with cloud infrastructure such as AWS/Azure/GCP.
- Knowledge of databases, storage systems, and backup mechanisms.
- Basic scripting/programming using Python, Bash, or PowerShell.
- Understanding of server deployment and application hosting.
- Knowledge of monitoring and logging tools.
- Ability to troubleshoot hardware, software, networking, and infrastructure issues.

Preferred Skills

- Experience with GPU computing / NVIDIA CUDA / Jetson.
- Experience with edge computing and IoT systems.
- Knowledge of Kubernetes or other container orchestration platforms.
- Experience with CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, etc.
- Familiarity with Terraform, Ansible, or infrastructure-as-code practices.
- Experience with MQTT and IoT communication protocols.
- Knowledge of cybersecurity and system hardening.
- Experience supporting AI/ML or computer-vision applications.
- Experience working with industrial automation or embedded systems.

Educational Qualification:





Bachelor's/Master's degree in:

- Computer Science
- Information Technology
- Computer Engineering
- Electronics & Communication Engineering
- Electrical Engineering
- or a related technical discipline.

Experience

1-2 years of relevant experience in system administration, cloud computing, DevOps, infrastructure management, edge computing, or a related field.

Freshers with strong hands-on experience in Linux, cloud, Docker, networking, and computing infrastructure may also be considered for a junior position.

Key Competencies

- Solid analytical and troubleshooting skills
- Good understanding of computing architecture
- Ability to work across hardware and software environments
- Strong problem-solving and debugging capability
- Good documentation practices
- Ability to work independently and with cross-functional teams
- Willingness to support field deployments when required
- Strong ownership and learning attitude

Key Performance Indicators (KPIs)

- Server and infrastructure uptime
- Deployment reliability and success rate
- System performance and resource utilization
- Mean time to resolve infrastructure issues
- Backup and recovery reliability
- Security and system compliance
- CI/CD deployment efficiency
- Documentation completeness
- Successful deployment and maintenance of edge/field systems

What We Offer

- Opportunity to work on deep-tech, IoT, automation, AI/ML, and intelligent computing systems.
- Exposure to cloud, edge computing, industrial systems, and real-world technology deployments.
- Opportunity to work closely with multidisciplinary R&D; and engineering teams.
- A challenging workplace focused on building scalable technology solutions.

Pay: ₹20,000.00 - ₹25,000.00 per month

Benefits:

- Flexible schedule

Ability to commute/relocate:

- Jagatpur, Odisha: Reliably commute or planning to relocate before starting work (Preferred)

Application Question(s):

- What is edge computing, and how is it different from cloud computing?Use brain not chatgpt.
- What are the main challenges of deploying computing systems at the edge?
- Imagine we have an industrial/IoT system deployed at 100 sites. Each site has sensors, pumps, motors and an edge computer. Internet connectivity may go down for 6–12 hours. How would you design the system so that:

Local monitoring continues
Automation continues
Data is stored locally
Data synchronizes when connectivity returns
Remote engineers can troubleshoot the device

- If you were given a completely new edge-computing project tomorrow, what information would you need before selecting the hardware and designing the architecture?

Education:

- Bachelor's (Required)

Work Location: In person

📌 Edge Computing Specialist (India)
🏢 BARIFLO CYBERNETICS PRIVATE
📍 India