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2 Days ago

Python Full Stack Developer(Cloud&AI Integration)

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Bangalore, Karnataka, India
Information Technology
Full-Time
VectorStack

Overview

Skills:
Programming Languages, Backend Frameworks, Frontend Development, API & Microservices, Cloud & Serverless Computing, AI/ML Integration,

Python Full Stack Developer Cloud & AI Integration 3- 5 years

We are looking for a dynamic Python Full Stack Developer to join our engineering team. This role blends full stack development with cloud-native architecture and AI/data science integration. Youll work on scalable web applications, deploy intelligent services on AWS, and collaborate with data scientists to bring machine learning models into production.

Key Responsibilities

  • Develop and maintain scalable web applications using Python (Flask/Django/FastAPI) and modern JavaScript frameworks (ReactJS).
  • Design and implement RESTful APIs and microservices for AI-driven applications.
  • Integrate machine learning models and data pipelines into production environments.
  • Leverage AWS services (Lambda, S3, EC2, API Gateway, SageMaker) for cloud-native development.
  • Collaborate with data scientists and DevOps engineers to deploy and monitor AI solutions.
  • Ensure application security, performance, and scalability.
  • Participate in code reviews, agile ceremonies, and continuous improvement initiatives.

Required Skills

  • Proficiency in Python and JavaScript (React JS preferred).
  • Excellent problem-solving and communication skills.
  • Expert in Python Programming, Deployment of AI solutions and AI engineering
  • Experience with backend frameworks like Django, Flask, or FastAPI.
  • Solid understanding of AWS services and serverless architecture.
  • Familiarity with AI/ML workflows and tools (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
  • Strong problem-solving skills and ability to work in cross-functional teams.

Preferred Qualifications

  • Bachelors or Masters in Computer Science, Engineering, or related field.
  • Exposure to MLOps practices and tools (e.g., MLflow, SageMaker Pipelines).
  • Experience with data visualization libraries and BI tools.
  • Knowledge of data engineering concepts (ETL, data lakes, streaming).
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