Job highlights

- Experience with Python, FastAPI, microservices, SQL, MLOps, Docker, and Kubernetes

- Design and maintain scalable backend services, deploy AI/ML models, manage containerized applications, and automate CI/CD pipelines

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

- Solid hands-on experience with Python and FastAPI.

- Good 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.

- Strong 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