Backend Architecture Engineer

6 hours ago


vijayawada, India beBeeEngineering Full time

Backend Engineering LeadWe are seeking a seasoned Backend Engineering Lead to drive the development of our backend architecture, API engineering, and service orchestration using advanced proficiency in .Net and Python.Key Responsibilities:Lead the development of scalable and maintainable backend systems.Design and implement API frameworks using FastAPI, LangChain, and LangGraph.Develop and deploy cloud-based services on AWS or Azure, leveraging Bedrock, Lambda, ECS/EKS, Step Functions, S3, and SageMaker.Craft AI pipeline architectures, embedding pipelines, and vector search integrations (Pinecone, FAISS, ChromaDB).Engineer prompt strategies, retrieval algorithms, and dynamic context management.Collaborate with cross-functional teams to design and implement microservices, RESTful APIs, event-driven design, and asynchronous message queues (Kafka, SNS/SQS).Implement DevOps and CI/CD practices, containerization (Docker, Kubernetes), IaC (Terraform/CloudFormation), and automated deployment pipelines.Ensure security and compliance by designing IAM, data encryption, secure API gateways, and AI model governance standards.Requirements:Advanced proficiency in .Net and Python programming languages.Deep hands-on experience with FastAPI, LangChain, LangGraph, and LLM orchestration pipelines.Expert-level experience with AWS or Azure cloud architecture, particularly Bedrock, Lambda, ECS/EKS, Step Functions, S3, and SageMaker.Pronounced ability to design RAG architectures, embedding pipelines, and vector search integrations (e.g., Pinecone, FAISS, ChromaDB).Strong understanding of prompt chaining, retrieval strategies, and dynamic context management.Foundation in microservices, RESTful APIs, event-driven design, and asynchronous message queues (Kafka, SNS/SQS).Familiarity with containerization (Docker, Kubernetes), IaC (Terraform/CloudFormation), and automated deployment pipelines.Knowledge of IAM, data encryption, secure API gateways, and AI model governance standards.Bonus Points:Demonstrated expertise in AI pipeline design, RAG architectures, and vector search integrations.Experience with AI model governance standards and secure API gateways.



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