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Gleecus TechLabs - Python Developer - Django / FastAPI

Gleecus TechLabs - Python Developer - Django / FastAPI

GleecusHyderabad
30+ days ago
Job description

Job Title : Python Backend Engineer AWS | GenAI & ML.

Experience : 5 Years.

Employment Type : Full-Time.

Job Summary :

We are seeking an experienced Python Backend Engineer with strong AWS expertise and a background in AI / ML to build and scale intelligent backend systems and GenAI-driven applications.

The ideal candidate should have hands-on experience building REST APIs using Django or FastAPI and implementing AI / LLM applications using Langchain. Experience with LangGraph is a strong plus.

Key Responsibilities :

  • Design, develop, and maintain Python-based backend systems and AI-powered services.
  • Build and manage RESTful APIs using Django or FastAPI for AI / ML model integration.
  • Develop and deploy machine learning and GenAI models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Implement GenAI pipelines using Langchain; LangGraph experience is a plus.
  • Utilize AWS services including EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment.
  • Collaborate with data scientists, DevOps, and architects to integrate models and workflows into production.
  • Build and manage CI / CD pipelines for backend and model deployments.
  • Ensure performance, scalability, and security of applications in cloud environments.
  • Monitor production systems, troubleshoot issues, and optimize model and API performance.

Required Skills and Experience :

  • 5 years of hands-on experience in Python backend development.
  • Strong experience building RESTful APIs using Django or FastAPI.
  • Proficiency in AWS cloud services : EC2, S3, Lambda, SageMaker, CloudFormation, etc.
  • Solid understanding of ML / AI concepts and model deployment practices.
  • Experience with ML libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
  • Hands-on experience with Langchain for building GenAI applications.
  • Familiarity with DevOps tools : Docker, Kubernetes, Git, Jenkins, Terraform.
  • Good understanding of microservices architecture and CI / CD workflows.
  • Agile development experience.
  • Nice to Have :

  • Experience with LangGraph for agentic workflows or graph-based orchestration.
  • Knowledge of LLMs, embeddings, and vector databases (e.g., Pinecone, FAISS).
  • Exposure to OpenAI APIs, AWS Bedrock, or similar GenAI platforms.
  • Understanding of MLOps tools and practices for model monitoring, versioning, and retraining.
  • (ref : hirist.tech)

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