Gen AI developer(10+years of experience)
Role: Gen AI developer
Location: Remote, it will be nice to have local to St Louis...
Open on both w2 and c2c.
Skills for a Generative AI Developer
Communication and Collaboration Skills
Ā Ability to communicate and collaborate with other programmers, researchers, or stakeholders, and be able to explain the technical details, challenges, and results of their generative AI projects.
Ā Ability to work in a highly dynamic fast paced environment were priorities can change frequently.
Architecture and Design Skills
Ā Should have a strong background in computer science, mathematics, and statistics, as well as a solid understanding of the principles and techniques of machine learning and deep learning.
Ā Should be proficient in programming languages, such as Python, and relative frameworks that are commonly used for developing and deploying generative AI models.
Ā Should be familiar with the state-of-the-art research and developments in generative AI, such as the latest models, architectures, algorithms, and datasets.
Ā Ability to take an idea from conception to delivery, working with team members to ideate creative, low-cost, iterative solutions to requested features and defects.
Python Knowledge
Ā Core Python Concepts
Ā Proficiency in Python syntax and semantics
Ā Understanding of data types, variables, and operators
Ā Mastery of control structures (if statements, loops)
Ā Knowledge of functions, lambdas, and higher-order functions
Ā Familiarity with modules and packages
Ā Object-Oriented Programming (OOP)
Ā Understanding of classes, objects, inheritance, polymorphism, and encapsulation
Ā Ability to design and implement class hierarchies
Ā Error Handling and Exceptions
Ā Understanding of exception handling using try, except, finally blocks
Ā Ability to create custom exceptions
Ā File I/O
Ā Reading from and writing to files
Ā Working with different file formats (e.g., CSV, JSON)
FastAPI Knowledge
Ā API Development
Ā Building RESTful APIs using FastAPI
Ā Creating and handling endpoints (GET, POST, PUT, DELETE)
Ā Request Validation and Serialization
Ā Using Pydantic models for data validation and serialization
Ā Implementing request and response models
Ā Dependency Injection
Ā Understanding FastAPI's dependency injection system
Ā Creating and using dependencies
Ā Asynchronous Programming
Ā Writing asynchronous endpoints with async/await
Ā Understanding the event loop and concurrency
Ā Middleware and CORS
Ā Creating and using middleware
Ā Configuring Cross-Origin Resource Sharing (CORS)
LangChain Knowledge
Ā Integrating Language Models
Ā Understanding the purpose and functionality of LangChain
Ā Building applications that integrate language models with various tools and data sources
Ā Chain Management
Ā Creating and managing chains of tools and models
Ā Implementing complex workflows using LangChain
Ā Tool Executors
Ā Understanding the concept of Executors in LangChain
Ā Designing use cases that benefit from Executors
AWS Knowledge
Ā Serverless Architecture
Ā Understanding the principles of serverless computing
Ā Designing and deploying AWS Lambda functions
Ā Event-Driven Programming
Ā Creating and managing event sources for Lambda functions (e.g., S3, DynamoDB, API Gateway)
Ā Handling events and triggers
Ā Lambda Configuration and Deployment
Ā Setting up Lambda execution roles and permissions
Ā Deploying Lambda functions using AWS Management Console, CLI, and infrastructure as code (e.g., AWS CloudFormation, Terraform)
OAuth2 Flows Knowledge
Ā OAuth2 Fundamentals
Ā Understanding the OAuth2 authorization framework
Ā Familiarity with key concepts: access tokens, refresh tokens, scopes
Ā OAuth2 Flows
Ā Knowledge of different OAuth2 flows: Authorization Code Flow, Client Credentials Flow, Implicit Flow, and Resource Owner Password Credentials Flow
Ā Implementing OAuth2 authentication and authorization in applications
Ā Token Management
Ā Handling token generation, storage, and validation
Ā Implementing token refresh mechanisms
Additional Skills
Ā Version Control & CI/CD
Ā Proficiency with Git and version control practices
Ā Understanding and abilities to use Jenkins for CI/CD pipelines
Ā Testing and Debugging
Ā Writing unit tests and integration tests
Ā Using testing frameworks (e.g., pytest)
Ā Debugging techniques and tools
Ā Documentation
Ā Writing clear and comprehensive documentation
Ā Using tools like Swagger/OpenAPI for API documentation
Ā Collaboration Tools
Ā Experience with collaboration tools (e.g., JIRA, Confluence
Apply Now
Location: Remote, it will be nice to have local to St Louis...
Open on both w2 and c2c.
Skills for a Generative AI Developer
Communication and Collaboration Skills
Ā Ability to communicate and collaborate with other programmers, researchers, or stakeholders, and be able to explain the technical details, challenges, and results of their generative AI projects.
Ā Ability to work in a highly dynamic fast paced environment were priorities can change frequently.
Architecture and Design Skills
Ā Should have a strong background in computer science, mathematics, and statistics, as well as a solid understanding of the principles and techniques of machine learning and deep learning.
Ā Should be proficient in programming languages, such as Python, and relative frameworks that are commonly used for developing and deploying generative AI models.
Ā Should be familiar with the state-of-the-art research and developments in generative AI, such as the latest models, architectures, algorithms, and datasets.
Ā Ability to take an idea from conception to delivery, working with team members to ideate creative, low-cost, iterative solutions to requested features and defects.
Python Knowledge
Ā Core Python Concepts
Ā Proficiency in Python syntax and semantics
Ā Understanding of data types, variables, and operators
Ā Mastery of control structures (if statements, loops)
Ā Knowledge of functions, lambdas, and higher-order functions
Ā Familiarity with modules and packages
Ā Object-Oriented Programming (OOP)
Ā Understanding of classes, objects, inheritance, polymorphism, and encapsulation
Ā Ability to design and implement class hierarchies
Ā Error Handling and Exceptions
Ā Understanding of exception handling using try, except, finally blocks
Ā Ability to create custom exceptions
Ā File I/O
Ā Reading from and writing to files
Ā Working with different file formats (e.g., CSV, JSON)
FastAPI Knowledge
Ā API Development
Ā Building RESTful APIs using FastAPI
Ā Creating and handling endpoints (GET, POST, PUT, DELETE)
Ā Request Validation and Serialization
Ā Using Pydantic models for data validation and serialization
Ā Implementing request and response models
Ā Dependency Injection
Ā Understanding FastAPI's dependency injection system
Ā Creating and using dependencies
Ā Asynchronous Programming
Ā Writing asynchronous endpoints with async/await
Ā Understanding the event loop and concurrency
Ā Middleware and CORS
Ā Creating and using middleware
Ā Configuring Cross-Origin Resource Sharing (CORS)
LangChain Knowledge
Ā Integrating Language Models
Ā Understanding the purpose and functionality of LangChain
Ā Building applications that integrate language models with various tools and data sources
Ā Chain Management
Ā Creating and managing chains of tools and models
Ā Implementing complex workflows using LangChain
Ā Tool Executors
Ā Understanding the concept of Executors in LangChain
Ā Designing use cases that benefit from Executors
AWS Knowledge
Ā Serverless Architecture
Ā Understanding the principles of serverless computing
Ā Designing and deploying AWS Lambda functions
Ā Event-Driven Programming
Ā Creating and managing event sources for Lambda functions (e.g., S3, DynamoDB, API Gateway)
Ā Handling events and triggers
Ā Lambda Configuration and Deployment
Ā Setting up Lambda execution roles and permissions
Ā Deploying Lambda functions using AWS Management Console, CLI, and infrastructure as code (e.g., AWS CloudFormation, Terraform)
OAuth2 Flows Knowledge
Ā OAuth2 Fundamentals
Ā Understanding the OAuth2 authorization framework
Ā Familiarity with key concepts: access tokens, refresh tokens, scopes
Ā OAuth2 Flows
Ā Knowledge of different OAuth2 flows: Authorization Code Flow, Client Credentials Flow, Implicit Flow, and Resource Owner Password Credentials Flow
Ā Implementing OAuth2 authentication and authorization in applications
Ā Token Management
Ā Handling token generation, storage, and validation
Ā Implementing token refresh mechanisms
Additional Skills
Ā Version Control & CI/CD
Ā Proficiency with Git and version control practices
Ā Understanding and abilities to use Jenkins for CI/CD pipelines
Ā Testing and Debugging
Ā Writing unit tests and integration tests
Ā Using testing frameworks (e.g., pytest)
Ā Debugging techniques and tools
Ā Documentation
Ā Writing clear and comprehensive documentation
Ā Using tools like Swagger/OpenAPI for API documentation
Ā Collaboration Tools
Ā Experience with collaboration tools (e.g., JIRA, Confluence
Apply Now