01Key Responsibilities
Python Development:
- Design, develop, test, and maintain robust Python applications.
- Write clean, reusable, and scalable code following best practices.
- Develop REST APIs and microservices using frameworks such as FastAPI, Flask, or Django.
- Optimize application performance and troubleshoot production issues.
AI/ML Development:
- Build, train, evaluate, and deploy machine learning models.
- Develop data preprocessing, feature engineering, and model validation pipelines.
- Implement predictive analytics, classification, recommendation, and NLP solutions.
- Work with large datasets and model monitoring frameworks.
Generative AI :
- Design and implement GenAI solutions using Large Language Models (LLMs).
- Develop AI-powered chatbots, copilots, and intelligent automation solutions.
- Utilize frameworks such as LangChain, LlamaIndex, Semantic Kernel, and Hugging Face.
- Implement Prompt Engineering, RAG (Retrieval-Augmented Generation), Vector Databases, and AI Agent workflows.
- Integrate OpenAI, Azure OpenAI, Claude, Gemini, or open-source LLMs into enterprise applications.
DevOps & Cloud :
- Implement CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or GitLab.
- Containerize applications using Docker and orchestrate deployments using Kubernetes.
- Automate infrastructure provisioning using Infrastructure as Code (Terraform, ARM, CloudFormation).
- Monitor application health, performance, and security.
- Deploy and manage AI/ML solutions on Azure, AWS, or GCP.
Required Skills
Programming :
- Strong expertise in Python.
- Experience with Object-Oriented Programming (OOP), multithreading, and asynchronous programming.
- Knowledge of SQL and NoSQL databases.
AI/ML Frameworks:
- TensorFlow
- PyTorch
- Scikit-learn
- Keras
- XGBoost
Generative AI :
- OpenAI/Azure OpenAI Services
- LangChain
- LlamaIndex
- Hugging Face Transformers
- Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
- Prompt Engineering and RAG Architectures
DevOps Tools:
- Git/GitHub
- Azure DevOps
- Jenkins
- Docker
- Kubernetes
- Terraform
- CI/CD Pipeline Management
Cloud Platforms :
- Microsoft Azure (preferred)
- AWS
- Google Cloud Platform (GCP)
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
- 3+ years of Python development experience.
- 2+years of AI/ML or GenAI implementation experience.
- Experience with MLOps and model deployment.
- Relevant certifications in Azure AI, AWS AI/ML, Kubernetes, or DevOps. .
