What are the responsibilities and job description for the Senior Developer position at Satwic Inc?
QUALIFICATIONS AND DUTIES
1) Design and develop NLU application (chatbot) using Lex. Design Conversational Flow: Create a flowchart or diagram outlining the chatbot's conversation paths, responses, and possible user inputs.
2) Develop Natural Language Processing (NLP) Capabilities: Implement NLP models to enable the chatbot to understand and process user inputs effectively. Create intents and define slot types based on the application requirement. Set up how the lex bot conversation should flow and error handling. Use Lex's dialog management system to specify prompts for each slot and determine fallback responses. Use Lambda functions for dynamic responses or backend logic.
3) Thoroughly test the bot to ensure it responds accurately, handles edge cases, and performs smoothly in various situations. Use the built-in testing interface in the AWS Lex console to simulate conversations. Implement monitoring using Amazon CloudWatch to track bot performance and errors. Adjust intents, prompts, and Lambda functions as needed based on user feedback.
4) Use APIs to interact with different LLMs. Understand various LLMs available on Amazon Bedrock and how to invoke them efficiently and cost-optimized using customized completion prompts.
5) Use various AWS technologies like API G/W, Lambda, S3, CloudFormation scripts, CloudWatch, etc to create a complete solution that can be monitored, optimized, and updated with automation tools.
6) Write and Optimize Python Code. Develop clean, readable, and efficient Python code to solve problems or build applications. Continuously refactor code for readability and performance. Use libraries like collections, langchain, and built-in functions to optimize code. 7) Develop services using SOA and interact with APIs to send or receive data from external systems or services using libraries to make GET, POST, PUT, and DELETE requests. Create and process JSON requests and responses and manage authentication (like OAuth tokens or API keys).
8) Manage project dependencies and keep environments isolated for each project. Create application packages and docker images that can be deployed in a cloud infrastructure. Ensure all dependencies are packaged and use venv or virtualenv to create isolated Python environments for different projects.
9) Ensure code quality by writing tests and debugging issues that arise. Conduct thorough testing, including unit testing and user acceptance testing (UAT), to ensure the chatbot functions as expected and fix any bugs.
10) Use database concepts to write and create SQL queries to extract data from database.
1) Design and develop NLU application (chatbot) using Lex. Design Conversational Flow: Create a flowchart or diagram outlining the chatbot's conversation paths, responses, and possible user inputs.
2) Develop Natural Language Processing (NLP) Capabilities: Implement NLP models to enable the chatbot to understand and process user inputs effectively. Create intents and define slot types based on the application requirement. Set up how the lex bot conversation should flow and error handling. Use Lex's dialog management system to specify prompts for each slot and determine fallback responses. Use Lambda functions for dynamic responses or backend logic.
3) Thoroughly test the bot to ensure it responds accurately, handles edge cases, and performs smoothly in various situations. Use the built-in testing interface in the AWS Lex console to simulate conversations. Implement monitoring using Amazon CloudWatch to track bot performance and errors. Adjust intents, prompts, and Lambda functions as needed based on user feedback.
4) Use APIs to interact with different LLMs. Understand various LLMs available on Amazon Bedrock and how to invoke them efficiently and cost-optimized using customized completion prompts.
5) Use various AWS technologies like API G/W, Lambda, S3, CloudFormation scripts, CloudWatch, etc to create a complete solution that can be monitored, optimized, and updated with automation tools.
6) Write and Optimize Python Code. Develop clean, readable, and efficient Python code to solve problems or build applications. Continuously refactor code for readability and performance. Use libraries like collections, langchain, and built-in functions to optimize code. 7) Develop services using SOA and interact with APIs to send or receive data from external systems or services using libraries to make GET, POST, PUT, and DELETE requests. Create and process JSON requests and responses and manage authentication (like OAuth tokens or API keys).
8) Manage project dependencies and keep environments isolated for each project. Create application packages and docker images that can be deployed in a cloud infrastructure. Ensure all dependencies are packaged and use venv or virtualenv to create isolated Python environments for different projects.
9) Ensure code quality by writing tests and debugging issues that arise. Conduct thorough testing, including unit testing and user acceptance testing (UAT), to ensure the chatbot functions as expected and fix any bugs.
10) Use database concepts to write and create SQL queries to extract data from database.
