Python Developer

Role Overview

Were seeking a seasoned Lead Python Developer with a strong foundation in building scalable backend systems, developing MLOps workflows, and a keen interest in working with cutting-edge technologies in the Large Language Model (LLM) space.

Key Responsibilities:

MLOps & LLM Engineering

• Design, implement, and maintain MLOps pipelines for model training, evaluation, deployment, and monitoring.
• Collaborate with ML engineers and data scientists to productionize LLM-powered solutions.
• Engage in research, prototyping, and implementation of LLM-based functionalities.

Architecture & Scalability

• Make architectural decisions to ensure systems are highly available, fault-tolerant, and scalable.
• Continuously optimize performance, scalability, and cost-efficiency of backend and ML systems.

Collaboration & Product Impact

• Partner with product managers, designers, and cross-functional stakeholders to deliver impactful features.
• Promote best practices in Python development, testing, deployment, and code quality.

What Were Looking For

Technical Expertise

• 8+ years of experience in production-level backend development using Python.
• Proficiency in FastAPI , asynchronous programming, microservices architecture, and RESTful API development.
• Strong experience with message queues and data pipelines (e.g., Kafka, RabbitMQ).
• Deep understanding of scalable architectures (horizontal scaling, caching, sharding, etc.).
• Solid hands-on experience with MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, or Vertex AI.
• Familiarity with LLM architectures, fine-tuning techniques, and vector database integration.
• Exposure to tools and frameworks in the LLM space such as LangChain, Haystack, or similar is a plus.

Soft Skills & Collaboration

• Proven leadership and mentoring skills.
• Strong problem-solving ability and product-oriented thinking.
• Excellent communication and collaboration with cross-functional teams.