Senior Python Engineer

Easetalent is a premier recruiting and consulting firm dedicated to connecting top-tier talent with exceptional career opportunities. Our mission is to drive growth and success for both our candidates and partner companies by bridging the talent-opportunity gap.

A Senior Python Engineer with AI expertise is responsible for designing, developing, and deploying scalable Python applications that integrate artificial intelligence solutions. Key duties include building AI models, automating data pipelines, using frameworks like TensorFlow or PyTorch, and deploying and optimizing large language models (LLMs). This role requires strong Python programming skills, expertise in machine learning algorithms, experience with vector databases, and familiarity with cloud platforms and containerization tools like Docker.

Key responsibilities:

• Develop and maintain AI-driven applications: Design, build, and deploy scalable Python applications that integrate AI functionalities.
• Build and optimize AI models: Develop and implement AI-driven applications using advanced AI/ML frameworks like TensorFlow, PyTorch, and libraries such as LangChain. 
• Deploy and optimize LLMs: Deploy and optimize large language models (LLMs) in production environments, ensuring scalability and performance.
• Design and develop Python-based ETL tools and frameworks like Celery, Airflow, Pandas and pySpark.
• Use vector databases: Utilize and optimize vector databases for efficient management of high-dimensional data in AI/ML applications.
• Backend development: Develop backend services, including API integrations, database models (e.g., PostgreSQL), and connecting to third-party services.
• Mentorship and best practices: Mentor junior engineers, conduct code reviews, and implement best practices in coding, testing, and deployment.
• Collaborate with teams: Work with cross-functional teams to gather
  requirements, align technical specifications with business goals, and provide technical guidance.
• Cloud and containerization: Leverage AWS for training and deployment, and use tools like Docker and Kubernetes for containerization and orchestration.

Required skills and qualifications:

• Programming: Strong proficiency in Python and its scientific libraries (NumPy, Pandas, SciPy).
• AI/ML: Deep understanding of machine learning algorithms (supervised,
  unsupervised, reinforcement learning) and deep learning frameworks
  (TensorFlow, PyTorch, Keras).
• Agentic AI Concepts: Strong grasp of core concepts like Reasoning Models , Tool Calling , MCP and agentic AI development experience.
  Data handling: Experience with databases, including relational databases, NoSQL, and vector databases (e.g., Chroma, Pinecone, Milvus).
• Cloud computing: Experience with cloud platforms like AWS, GCP, or Azure.
• Containerization: Familiarity with Docker and container orchestration platforms like Kubernetes.
• LLM frameworks: Experience with AI agent frameworks like Hugging face Transformer library , vLLM , LangChain, or LangGraph is highly preferred.
• Experience: Typically 5-7+ years of experience in software development, with a focus on AI/ML in an industrial or production setting