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'll leverage 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 / :
- Design and implement core backend services and APIs for the 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, 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 cross-functional team members, including DevOps, product, and frontend engineers.
- Stay current with the latest advancements in LLMs and AI agent :
- 4+ 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 / LangGraphor are similar LLM orchestration frameworks.
- Strong knowledge 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 an 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.(ref : hirist.tech)