Description

Key Skills: Python, GCP, FastAPI, BigQuery, Docker, Kubernetes, LLM Integration, RAG Pipelines, Microservices, REST APIs

Good to Have Skills: Flask, Django, AsyncIO, Vertex AI, Cloud Run, GKE, Cloud Functions, Compute Engine, Cloud Storage, PostgreSQL, MySQL, MongoDB, CI/CD pipelines, GitHub Actions, Cloud Build, Jenkins, TensorFlow, PyTorch, LangChain, Hugging Face, Prompt Engineering, Vector Databases, Pinecone, FAISS, Message Queues, Pub/Sub, Kafka, MLOps, GCP Certification

Roles & Responsibilities:

• Design and develop backend services to power AI-driven applications with scalable architecture.
• Integrate Large Language Models (LLMs) and ML models into production systems for optimal performance.
• Build RESTful APIs and microservices using Python frameworks like FastAPI, Flask, or Django.
• Implement RAG (Retrieval-Augmented Generation) pipelines and AI orchestration workflows for intelligent applications.
• Design and deploy AI backend services on Google Cloud Platform using various GCP services.
• Ensure scalability, monitoring, and fault tolerance of cloud applications in production environments.
• Develop data pipelines to support AI models and analytics workflows for enterprise applications.
• Containerize applications using Docker and deploy services using Kubernetes on GKE platform.
• Implement CI/CD pipelines using GitHub Actions, Cloud Build, or Jenkins for automated deployments.
• Participate in Agile/Scrum ceremonies and conduct peer code reviews for quality assurance.

Experience Required: 5.5 to 9 years of backend development experience with strong proficiency in Python and hands-on experience with GCP cloud services. Experience building scalable backend systems, APIs, and knowledge of microservices architecture required.

Education: Bachelor's or Master's degree in Computer Science, Engineering, or related field

Key Skills

Education

Any Graduate