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Posted:8 hours ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Job purpose:


Design & implement the best-engineered technical solutions using the latest technologies and tools.


Who You Are:


  • Lead Python development efforts for GenAI and data engineering projects from architecture to deployment.
  • Build and optimize LLM-powered pipelines, APIs, and services using OpenAI, Hugging Face, or similar frameworks.
  • Architect and implement scalable data pipelines, transformation logic, and feature engineering for AI models.
  • Collaborate with ML/AI scientists, data engineers, and product teams to deliver end-to-end GenAI solutions.
  • Drive the integration of LLMs into real-time applications (e.g., chatbots, summarizers, copilots).
  • Design and maintain efficient, reusable, and reliable Python code using modern frameworks (FastAPI, Django).
  • Ensure high code quality through unit testing, code reviews, and adherence to best practices.
  • Optimize performance, cost, and scalability of AI-powered backend systems in cloud-native environments.
  • Provide technical guidance and mentorship to junior engineers.



What will excite us:


  • 5+ years of professional experience in Python backend development.


  • 2+ years of experience working with GenAI / LLMs (OpenAI, Hugging Face, LangChain, etc.).


  • Hands-on experience with FastAPI, Django, or Flask for scalable API development.


  • Strong experience in data engineering: ETL pipelines, data wrangling, feature engineering, and processing large datasets.


  • Experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS) and embedding models.


  • Solid grasp of asynchronous programming, RESTful API design, and microservices.


  • Proficiency with SQL/NoSQL databases, data lakes, and cloud platforms (AWS/GCP/Azure).


  • Familiarity with CI/CD pipelines, Docker, and container orchestration (Kubernetes is a plus).


  • Excellent communication and leadership skills with experience mentoring teams or leading projects.


What will excite you:


  • Experience with LangChain, LLMOps, or RAG (Retrieval-Augmented Generation) systems.
  • Exposure to MLOps tools like MLflow, Kubeflow, or Vertex AI.
  • Knowledge of data governance, privacy, and compliance in AI applications.
  • Contributions to open-source projects in Python, AI/ML, or data engineering domains.



Work location:

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