Backend Engineer - Artificial Intelligence

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 / LangGraph.

Responsibilities :

- 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, 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 cross-functional team members, including DevOps, product, and frontend engineers.

- Stay current with the latest advancements in LLMs and AI agent architectures.

Requirements :

- 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.