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Gen AI developer(10+years of experience)

Remote Full-time Live

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

  • 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.
  • Ability to work in a highly dynamic fast paced environment were priorities can change frequently. Architecture and Design Skills
  • 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.
  • Should be proficient in programming languages, such as Python, and relative frameworks that are commonly used for developing and deploying generative AI models.
  • Should be familiar with the state-of-the-art research and developments in generative AI, such as the latest models, architectures, algorithms, and datasets.
  • 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
  • Core Python Concepts
  • Proficiency in Python syntax and semantics
  • Understanding of data types, variables, and operators
  • Mastery of control structures (if statements, loops)
  • Knowledge of functions, lambdas, and higher-order functions
  • Familiarity with modules and packages
  • Object-Oriented Programming (OOP)
  • Understanding of classes, objects, inheritance, polymorphism, and encapsulation
  • Ability to design and implement class hierarchies
  • Error Handling and Exceptions
  • Understanding of exception handling using try, except, finally blocks
  • Ability to create custom exceptions
  • File I/O
  • Reading from and writing to files
  • Working with different file formats (e.g., CSV, JSON) FastAPI Knowledge
  • API Development
  • Building RESTful APIs using FastAPI
  • Creating and handling endpoints (GET, POST, PUT, DELETE)
  • Request Validation and Serialization
  • Using Pydantic models for data validation and serialization
  • Implementing request and response models
  • Dependency Injection
  • Understanding FastAPI's dependency injection system
  • Creating and using dependencies
  • Asynchronous Programming
  • Writing asynchronous endpoints with async/await
  • Understanding the event loop and concurrency
  • Middleware and CORS
  • Creating and using middleware
  • Configuring Cross-Origin Resource Sharing (CORS) LangChain Knowledge
  • Integrating Language Models
  • Understanding the purpose and functionality of LangChain
  • Building applications that integrate language models with various tools and data sources
  • Chain Management
  • Creating and managing chains of tools and models
  • Implementing complex workflows using LangChain
  • Tool Executors
  • Understanding the concept of Executors in LangChain
  • Designing use cases that benefit from Executors AWS Knowledge
  • Serverless Architecture
  • Understanding the principles of serverless computing
  • Designing and deploying AWS Lambda functions
  • Event-Driven Programming
  • Creating and managing event sources for Lambda functions (e.g., S3, DynamoDB, API Gateway)
  • Handling events and triggers
  • Lambda Configuration and Deployment
  • Setting up Lambda execution roles and permissions
  • Deploying Lambda functions using AWS Management Console, CLI, and infrastructure as code (e.g., AWS CloudFormation, Terraform) OAuth2 Flows Knowledge
  • OAuth2 Fundamentals
  • Understanding the OAuth2 authorization framework
  • Familiarity with key concepts: access tokens, refresh tokens, scopes
  • OAuth2 Flows
  • Knowledge of different OAuth2 flows: Authorization Code Flow, Client Credentials Flow, Implicit Flow, and Resource Owner Password Credentials Flow
  • Implementing OAuth2 authentication and authorization in applications
  • Token Management
  • Handling token generation, storage, and validation
  • Implementing token refresh mechanisms Additional Skills
  • Version Control & CI/CD
  • Proficiency with Git and version control practices
  • Understanding and abilities to use Jenkins for CI/CD pipelines
  • Testing and Debugging
  • Writing unit tests and integration tests
  • Using testing frameworks (e.g., pytest)
  • Debugging techniques and tools
  • Documentation
  • Writing clear and comprehensive documentation
  • Using tools like Swagger/OpenAPI for API documentation
  • Collaboration Tools
  • Experience with collaboration tools (e.g., JIRA, Confluence Apply Job!

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