Senior Software Engineer
Tasks
- Apply MLOps practices
- Build cloud native software applications
- Build reusable APIs and services
- Define cloud architecture on AWS
- Design Agentic AI systems
- Develop AI-enabled workflows
- Evaluate and improve agent performance
- Implement observability and monitoring
- Implement retrieval-augmented generation
- Integrate large language models into production apps
- Operationalize machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
API | AWS | Agentic AI | Amazon SageMaker | Apache Airflow | Autogen | CI/CD | Cloud Native | Databricks | Docker | Embeddings | Error Handling | Event Driven | Event-driven architecture | JavaScript | Kubeflow | Kubernetes | LLM integration | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | Logging | MLOps | MLflow | Microservices | Model Deployment | Model Evaluation | Model Monitoring | Model versioning | Monitoring | NoSQL | Observability | Performance optimization | Prompt engineering | Python | Reranking | Retrieval-Augmented Generation | SQL | Semantic Kernel | Semantic Search | Serverless | Testing | TypeScript | Vector Databases | Vector Search | Workflow Orchestration
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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