AI Operations Engineer
PradeepIT Consulting Services Pvt LtdPune, Maharashtra, India
Posted January 5, 2026
Full Time
About the Company
PradeepIT Consulting Services Pvt Ltd (PGC Digital) delivers end‑to‑end digital transformation and IT staffing solutions for enterprise clients worldwide. Leveraging partnerships with SAP, Microsoft, Salesforce and ServiceNow, the company offers on‑demand staff augmentation, AI‑enabled talent acquisition, greenfield and migration projects, and managed support services that are certified to CMMI Level 3, ISO 9001 and ISO 27001 standards. Its people‑first culture, recognized as a Great Place to Work and India’s Best Workplace for Women, fuels a collaborative approach that positions PGC Digital as a trusted extension of its customers’ teams. With a global delivery network spanning India, Canada, the U.S., and a Singapore regional hub, the firm is scaling toward a public listing in 2026 to accelerate growth and deliver long‑term value.
Job Description
The AI Operations Engineer will be responsible for deploying and managing AI/ML models, implementing automated CI/CD pipelines, and ensuring efficient model integration into existing enterprise applications and workflows. The role will also involve monitoring and performance management, automation and MLOps best practices, security and compliance, and collaboration and process improvement.
Requirements
- 3-5 years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions
- Bachelors or Masters degree in Computer Science, Data Engineering, AI, or a related field
- Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus
- Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments
- Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI
- Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow
- Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking
- Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads
- Familiarity with automation scripting using Python, Bash, or PowerShell
- Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization
- Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment
- Strong understanding of AI security principles, including data privacy and governance considerations
Benefits
- Competitive salary
- Opportunities for professional growth and development
- Collaborative and dynamic work environment