GenAI Architect

Overview

On Site
Depends on Experience
Full Time
No Travel Required

Skills

LLMs
prompt engineering

Job Details

Role : Gen AI Architect
San Jose, CA
Key Responsibilities
Solution Architecture
  • Design end-to-end generative AI systems (LLMs, diffusion models, multimodal systems) for enterprise use cases.
  • Architect scalable pipelines for text, image, audio, and video generation using frameworks like LangChain, Hugging Face, and custom models.
Model Strategy & Optimization
  • Fine-tune and deploy large language models (LLMs) (GPT-4, Llama, Claude) and diffusion models (Stable Diffusion, DALL-E).
  • Optimize models for performance, cost, and ethical alignment (bias mitigation, hallucination control).
Technical Leadership
  • Define best practices for prompt engineering, RAG (Retrieval-Augmented Generation), and model evaluation.
  • Mentor data scientists and engineers in generative AI techniques.
Integration & MLOps
  • Implement CI/CD pipelines for generative AI using MLFlow, Kubeflow, or Vertex AI.
  • Integrate solutions with cloud platforms (AWS Bedrock, Azure OpenAI, Google Cloud Platform Vertex).
Innovation & Ethics
  • Research emerging tech (agentic systems, autonomous AI).
  • Establish governance frameworks for responsible AI (compliance, security, fairness).
Required Skills
Technical Expertise
  • Generative AI:
    • Hands-on experience with LLMs, GANs, VAEs, and transformer architectures.
    • Proficiency in LangChain, LlamaIndex, and vector databases (Pinecone, Chroma).
  • Coding: Python, PyTorch/TensorFlow, REST APIs.
  • Cloud Platforms: AWS/Azure/Google Cloud Platform AI services.
Certifications (Preferred)
  • AWS/Azure/Google Cloud Platform Machine Learning Specialty
  • NVIDIA Generative AI with LLMs
Soft Skills
  • Strategic thinking with ability to translate business needs to technical solutions.
  • Exceptional communication for stakeholder alignment.
Qualifications
  • Education: Master s/PhD in Computer Science, AI, or related field.
  • Experience:
    • 8+ years in AI/ML, including 3+ years in generative AI.
    • Proven track record in production-grade gen AI deployments.
    • Portfolio of projects (GitHub, whitepapers, patents).
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