Gen Al/Agentic Al Architect - 100% Remote

Overview

Remote
Hybrid
Accepts corp to corp applications
Contract - Independent
Contract - W2

Skills

Gen Al

Job Details

Role: Gen Al/Agentic Al Architect

Location: Remote

JD:

  • Deep understanding of Generative Al concepts: This includes techniques such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and other models used for data generation.
  • Proficiency in programming languages: This includes proficiency in Python, along with Al libraries and frameworks like TensorFlow, PyTorch, or Keras Experience with cloud platforms: This includes experience with cloud platforms, such as AWS or Azure, and knowledge of containerization and orchestration tools like Kubernetes.
  • Strong understanding of machine learning and deep learning methodologies: This includes deep generative models, autoregressive models, and reinforcement learning for generative tasks. Domain knowledge and problem-solving skills: The role requires the ability to understand specific industry domains and apply Al solutions to address real-world challenges.
  • Excellent communication and collaboration skills: This is necessary to effectively communicate complex Al concepts to both technical and non-technic. audiences.
  • Enterprise GenAI Architecture & Strategy: The role defines and evolves the architecture for Generative Al systems within an organization. This includes creating scalable and secure platforms for various business domains and use cases.
  • LLM Model Development & Deployment: The role leads the selection, fine-tuning, and deployment of large language models (LLMS) to ensure optimal
  • performance, precision, and scalability.
  • This involves working with various LLM models (like GPT, Claude, Gemini, or Llama) and related frameworks (e-g.. LangChain and Llama Index).
  • Data Pipeline & BLOps: The role designs and implements data and ML pipelines, including data cleansing, pre-processing, model training or fine-tunin, and feedback loops. It also involves designing and managing CI/CD pipelines in the Generative Al space, including LLMOPS.
  • Prompt Engineering & Model Optimization: The role develops advanced architectural patterns for prompt engineering and implements intent analysis techniques to enhance Al agent decision-making and user interactions.
  • This also includes optimizing models for performance and efficiency.
  • Cross-Functional Collaboration: The role collaborates closely with business teams, data scientists, software engineers, and other stakeholders to understand business needs and translate them into effective Generative Al architectures.
  • This also involves promoting best practices through knowledge sharing and training.
  • Security & Responsible Al: The role implements security measures and ensures compliance with ethical considerations and responsible Al practices. Th involves assessing and mitigating risks and promoting transparency and explainability.
  • Innovation & Thought Leadership: The role stays up-to-date on the latest trends and advancements in Generative Al technologies and identifies opportunities for their use within the organization. This also includes serving as a thought leader and influencing both technical strategies and executive level decisions.
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