Sr Developer - AI Application Backend

 AI Application Development 

• Design and develop backend services to power AI-driven applications. 

• Integrate Large Language Models (LLMs), ML models, or AI services into production systems. 

• Build RESTful APIs and microservices using Python frameworks (FastAPI, Flask, Django). 

• Implement RAG (Retrieval-Augmented Generation) pipelines and AI orchestration workflows where applicable. 

• Optimize AI inference performance, latency, and reliability. 

🔹 Cloud & Infrastructure (GCP) 

• Design and deploy AI backend services on Google Cloud Platform (GCP). 

• Work with GCP services such as: 

• BigQuery 

• Cloud Run 

• Cloud Functions 

• Compute Engine 

• GKE (Kubernetes Engine) 

• Cloud Storage 

• Vertex AI (preferred) 

• Ensure scalability, monitoring, and fault tolerance of cloud applications. 

• Implement IAM policies, security best practices, and environment isolation. 

🔹 Data & Integration 

• Develop data pipelines to support AI models and analytics workflows. 

• Integrate backend systems with third-party APIs and enterprise applications. 

• Work with SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, BigQuery). 

• Handle data validation, transformation, and preprocessing logic. 

🔹 DevOps & CI/CD 

• Containerize applications using Docker. 

• Deploy and manage services using Kubernetes (GKE preferred). 

• Implement CI/CD pipelines (GitHub Actions, Cloud Build, Jenkins). 

• Monitor application health and performance using logging and observability tools. 

🔹 Collaboration & Engineering Excellence 

• Participate in Agile/Scrum ceremonies. 

• Write clean, maintainable, well-documented code. 

• Conduct peer code reviews. 

• Troubleshoot and debug production issues. 

• Contribute to architectural decisions and continuous improvement.