Artificial Intelligence Specialist

Mandatory Skills:

Proposer’s Resource must have at least six (6) years of experience in providing

services as listed in the Statement of Work (SOW).

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