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Job Title: Generative AI Architect
Location: San Jose, CA (Onsite)
Client: HCL
Job Type: Contract
 
Job Summary:
We are looking for a visionary Generative AI Architect to lead the design, development, and deployment of cutting-edge GenAI solutions for a high-impact enterprise environment. The ideal candidate brings deep technical expertise in machine learning, large language models (LLMs), and cloud-native systems, combined with a strong grasp of enterprise requirements, ethical AI practices, and cross-functional collaboration.
This is a unique opportunity to shape the future of AI-powered innovation at the intersection of technology and business transformation.
 
Key Responsibilities:
Architecture & Design:

• Architect scalable, secure, and performant solutions for Generative AI use cases, including LLMs, diffusion models, and multi-modal AI.
• Define and document end-to-end solution blueprints that integrate GenAI with enterprise platforms, APIs, and data ecosystems.

Model Integration & Customization:

• Evaluate, fine-tune, and operationalize foundation models (e.g., OpenAI, Anthropic, open-source) for business-specific applications.
• Build workflows for training, prompt engineering, retrieval-augmented generation (RAG), and continuous model improvement.

Platform Development:

• Collaborate with engineering teams to develop and scale GenAI platforms and services.
• Ensure the platforms are robust in terms of scalability, observability, resilience, and regulatory compliance.

Governance & Risk Management:

• Develop AI governance frameworks that ensure responsible AI use aligned with ethical, legal, and privacy standards.
• Implement tooling for bias detection, explainability, security, and ongoing model monitoring.

Strategy & Collaboration:

• Work with cross-functional teams including product, data, infrastructure, and security to embed GenAI capabilities into enterprise workflows.
• Act as a thought leader, evangelizing GenAI strategy and best practices to internal stakeholders and executive leadership.

 
Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
• 8+ years in AI/ML system design and architecture, with at least 2 years of hands-on experience in Generative AI or LLM-based systems.
• Deep knowledge of transformer-based models, embeddings, tokenization, and generative AI pipelines.
• Proficiency with ML/AI frameworks and tools such as Hugging Face, LangChain, PyTorch, TensorFlow.
• Strong experience in cloud environments (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and DevOps (CI/CD).
• Understanding of AI compliance, data privacy, and governance concerns in a regulated enterprise environment.

 
Preferred Qualifications:

• Experience designing enterprise-scale ML/AI platforms or implementing MLOps pipelines.
• Familiarity with vector databases like Pinecone, FAISS, or Weaviate, and RAG architectures.
• Expertise in prompt engineering, few-shot learning, and human-in-the-loop solutions.
• Certifications in AI/ML architecture or cloud platforms (AWS Certified Solutions Architect, etc.) are a plus.