Posted:11 hours ago|
Platform:
Work from Office
Full Time
We are seeking AI Backend Engineers to play a pivotal role in building our Agentic Workflow Service and Retrieval-Augmented Generation (RAG) Service. In this hybrid role, you'llleverage your expertise in both backend development and machine learning to create robust, scalable AI-powered systems using AWS Kubernetes, Amazon Bedrock models, AWS Strands Framework, and LangChain / LangGraph.
Understanding of and expertise in:
Design and implement core backend services and APIs for agentic framework and RAG systems
LLM-based applications using Amazon Bedrock models
RAG systems with advanced retrieval mechanisms and vector database integration
Implement agentic workflows using technologies such as AWS Strands Framework, LangChain / LangGraph
Design and develop microservices that efficiently integrate AI capabilities
Create scalable data processing pipelines for training data and document ingestion
Optimize model performance, inference latency, and overall system efficiency
Implement evaluation metrics and monitoring for AI components
Write clean, maintainable, and well-tested code with comprehensive documentation
Collaborate with multiple multi-functional team members including DevOps, product, and frontend engineers
Stay ahead of with the latest advancements in LLMs and AI agent architectures
Minimum experience requirements
6+ years of total software engineering experience
Backend development experience with strong Python programming skills
Experience in ML/AI engineering, particularly with LLMs and generative AI applications
Experience with microservices architecture, API design, and asynchronous programming
Demonstrated experience building RAG systems and working with vector databases
LangChain/LangGraph or similar LLM orchestration frameworks
Solid understanding of AWS services, particularly Bedrock, Lambda, and container services
Experience with containerization technologies and Kubernetes
Understanding of ML model deployment, serving, and monitoring in production environments
Knowledge of prompt engineering and LLM fine-tuning techniques
Excellent problem-solving abilities and system design skills
Strong communication skills and ability to explain complex technical concepts
Experience in Kubernetes, AWS Serverless
Experience in working with Databases (SQL, NoSQL) and data structures
Ability to learn new technologies quickly
Preferred Qualifications:
Must have AWS certifications - Associate Architect / Developer / Data Engineer / AI Track
Must have familiarity with streaming architectures and real-time data processing
Must have experience with ML experiment tracking and model versioning
Must have understanding of ML/AI ethics and responsible AI development
Experience with AWS Strands Framework
Knowledge of semantic search and embedding models
Contributions to open-source ML/AI projects
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