We are looking for a skilled Platform Engineer with experience in Python, FastAPI, microservices architecture, SQL, AI/ML, and MLOps. The ideal candidate will be responsible for developing scalable backend services, building and deploying AI/ML solutions, and managing containerized applications using Docker and Kubernetes.

Key Responsibilities
Design, develop, and maintain scalable backend applications using Python and FastAPI.
Build and manage microservices-based architectures and RESTful APIs.
Develop and optimize SQL queries, database schemas, and data access layers.
Implement MLOps practices for machine learning model deployment, monitoring, and lifecycle management.
Integrate AI/ML models and AI-powered capabilities into production applications.
Containerize applications using Docker and deploy them using Kubernetes.
Automate build, testing, deployment, and release processes using CI/CD pipelines.
Monitor application performance, troubleshoot production issues, and improve system reliability.
Collaborate with data scientists, AI engineers, DevOps teams, and software developers.
Follow best practices for security, scalability, performance, and maintainability.

Must-Have Skills
Robust hands-on experience with Python and FastAPI.




Valuable understanding of microservices architecture and REST API development.
Proficiency in SQL and relational databases.
Practical experience with MLOps, including model deployment, monitoring, and versioning.
Understanding of AI/ML concepts and integration of AI models into applications.
Hands-on experience with Docker for application containerization.
Experience deploying and managing applications using Kubernetes.
Knowledge of CI/CD pipelines, Git, and automated deployment practices.
Robust debugging, problem-solving, and analytical skills.

Good-to-Have Skills
Experience with cloud platforms such as AWS, Azure, or GCP.
Familiarity with MLflow, Kubeflow, or similar MLOps tools.
Knowledge of model serving, model monitoring, and workflow orchestration.
Experience with message brokers such as Kafka or RabbitMQ.
Familiarity with logging, monitoring, and observability tools such as Prometheus and Grafana.

Qualifications
Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
Relevant hands-on experience in backend engineering, platform engineering, AI/ML engineering, or MLOps.

📌 Platform Engineer Python +mlops Gurugram
🏢 Kezan consulting
📍 Gurugram