DevOps Engineer

DevOps Engineer (with AI Product Development Focus)

Experience Level: 3–4 Years

Location: Onsite

Department: Technology, Cloud & AI Automation

Reports To: Lead DevOps Engineer / Head of Engineering

About the Role

We are seeking a versatile and proactive DevOps Engineer skilled in managing modern cloud environments (AWS, GCP, Azure) and eager to actively contribute to the life cycle of AI-powered software product development. This position is ideal for candidates passionate about driving automation, reliability, and scalability in production systems, with the additional opportunity to directly innovate on our AI-enhanced product roadmap.

When DevOps workloads are low, you will play a significant role in building AI-driven product features or internal tools using modern AI development frameworks and platforms.

Key Responsibilities

DevOps and Infrastructure (Primary)

• Cloud Infrastructure Management: Design, deploy, and manage scalable, secure, and high-availability infrastructure across AWS, GCP, and Azure.
• CI/CD Pipeline Development: Build and maintain robust continuous integration and deployment pipelines (Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps).
• Infrastructure as Code (IaC): Implement and manage infrastructure using Terraform, CloudFormation, or Ansible.
• Containerization & Orchestration: Deploy, scale, and monitor microservices using Docker and Kubernetes (EKS, GKE, AKS).
• Monitoring & Logging: Implement observability solutions (Prometheus, Grafana, ELK/OpenSearch, CloudWatch) for proactive performance tracking and alerting.
• Automation & Scripting: Automate recurring tasks and workflows using Python, Bash, or PowerShell; prioritize code reusability and maintainability.
• Security & Compliance: Enforce cloud/application security best practices (IAM, vulnerability assessments, compliance automation).
• AI in DevOps: Experiment with and implement AI/ML-driven DevOps solutions-predictive deployment analytics, intelligent incident response, automated resource scaling.

AI-based Product Development (Secondary-when DevOps workload is light)

• AI Tool Integration: Develop or enhance internal tools and product features using LLMs and AI platforms (e.g., OpenAI, AWS SageMaker, GCP Vertex AI, Azure ML).
• Data Pipeline Automation: Build and automate pipelines to streamline data ingestion and model deployment.
• Prototyping: Contribute to prototyping AI-powered product modules or MVPs, collaborating with software and data engineering teams.
• AI Workflow Support: Support feature engineering, model evaluation, or integration of ML ops practices into the product stack.
• Technical Documentation: Create technical documentation and user guides for the AI-driven functionalities and tools developed.

Required Skills and Qualifications

• Bachelor's degree in Computer Science, IT, or relevant field.
• 3–4 years of DevOps, Cloud Infrastructure, and CI/CD implementation experience.
• Proficient with at least one major cloud provider (AWS, GCP, Azure).
• Familiarity with container orchestration (Kubernetes, Docker).
• Experience in at least one scripting/programming language-Python preferred.
• Prior engagement with AI/ML tools/platforms (e.g., OpenAI API, SageMaker, Vertex AI, or custom LLM solutions).
• Familiarity with software development frameworks , Python Flask/FastAPI, Java Spring Boot).
• Excellent communication, teamwork, and problem-solving skills.

Desirable / Nice-to-Have

• Knowledge of ML Ops, AI Ops, or DevSecOps practices.
• Demonstrated experience building software products using AI platforms or tools.
• Relevant certifications in DevOps or AI/cloud technologies.
• Willingness to lead internal workshops or brown-bag sessions to further AI skills within the DevOps team.

Salary Range

₹6,50,000 - ₹11,00,000 per annum

Job Type: Full-time

Pay: ₹650, ₹1,100,000.00 per year

Benefits:

• Food provided
• Paid sick time
• Paid time off
• Provident Fund
• Work from home

Ability to commute/relocate:

• Sreekaryam, Thiruvananthapuram, Kerala: Reliably commute or planning to relocate before starting work (Required)

Experience:

• DevOps: 3 years (Required)

Work Location: In person