Job Description: AI Architect cum Data Scientist (LLM & Applied AI)

Role Title: AI Architect cum Data Scientist
Location: San Jose, CA (Preferred Hybrid, 3 days/week onsite)
Employment Type: Contract

Role Overview

We are seeking a highly experienced AI Architect cum Data Scientist with strong expertise in Generative AI, Large Language Models (LLMs), Machine Learning, and Advanced Analytics. The ideal candidate will have hands-on experience designing, training, fine-tuning, and deploying production-grade AI/LLM solutions for complex enterprise use cases.

This role requires both strategic architecture capabilities and deep technical execution skills across the AI/ML lifecycle, including data engineering, model optimization, experimentation, evaluation, and scalable deployment.

Preference will be given to candidates located in or willing to work onsite in San Jose, CA (3 days/week). Exceptional candidates from other U.S. locations may also be considered.

Key Responsibilities

• Design and architect enterprise-scale AI/ML and Generative AI solutions.
• Build, train, fine-tune, and optimize Large Language Models (LLMs) for domain-specific applications.
• Make architectural decisions around:
  • Model selection
  • Data generation strategies
  • Training pipelines
  • Data governance and usage
  • Retrieval-Augmented Generation (RAG)
  • Prompt engineering frameworks
• Develop and deploy production-ready AI applications using LLMs and modern ML frameworks.
• Work hands-on with structured and unstructured data for analytics, feature engineering, and model development.
• Lead end-to-end ML lifecycle activities including experimentation, evaluation, deployment, monitoring, and optimization.
• Collaborate with engineering, product, and business teams to translate complex requirements into scalable AI solutions.
• Implement best practices for AI scalability, performance, observability, and responsible AI usage.
• Evaluate open-source and commercial LLM ecosystems and recommend optimal solutions.
• Mentor teams on AI/ML architecture, data science methodologies, and MLOps best practices.

Required Skills & Experience

Core Requirements

• 10+ years of experience in Data Science, AI/ML, or Advanced Analytics.
• Strong hands-on expertise in:
  • Machine Learning
  • Deep Learning
  • Predictive Analytics
  • Statistical Modeling
  • NLP
• Proven experience with:
  • LLM fine-tuning
  • Model training
  • Synthetic data generation
  • Embedding models
  • RAG architectures
  • Vector databases
• Demonstrated success taking LLM-based complex use cases into production environments.
• Strong understanding of AI data pipelines, model evaluation, and governance.

Technical Skills

• Python, SQL, PySpark
• TensorFlow / PyTorch
• Hugging Face Transformers
• LangChain / LlamaIndex
• OpenAI, Anthropic, or open-source LLM ecosystems
• Vector databases such as Pinecone, Weaviate, FAISS, ChromaDB
• Cloud platforms: AWS / Azure / Google Cloud Platform
• MLOps tools and CI/CD pipelines
• Docker, Kubernetes

Preferred Qualifications

• Experience architecting enterprise AI platforms.
• Experience with multi-agent AI systems.
• Knowledge of responsible AI, AI safety, and compliance frameworks.
• Strong communication and stakeholder management skills.
• Experience working in fast-paced product or consulting environments.

Nice to Have

• Experience with multimodal AI models.
• Exposure to reinforcement learning or RLHF.
• Experience optimizing inference performance and GPU utilization.
• Prior experience in enterprise AI transformation initiatives.

Work Arrangement

• Preferred Location: San Jose, CA
• Hybrid Model: 3 days/week onsite
• Open to exceptional candidates across other U.S. locations.