Fractal
Fractal
Fractal provides artificial intelligence, engineering, and design solutions for enterprise decision-making, serving Fortune 500 companies across industries including marketing, healthcare, and logistics. Its expertise spans marketing analytics, advanced analytics, predictive analytics, and customer analytics, supported by products such as Crux Intelligence, Eugenie.ai, Asper.ai, and Senseforth.ai. With more than 4,000 employees across global locations, Fractal brings together analytics and AI capabilities for organizations seeking data-driven approaches to complex business challenges.

Principal Data Scientist – Generative AI

Lead secure, scalable Generative AI architecture using LLMs, RAG, AI agents, and cloud platforms. Shape AI transformation for enterprise clients through solution design, governance, and executive stakeholder leadership.

Description

  • Design end-to-end Generative AI architectures spanning LLMs, RAG, AI agents, vector databases, and multimodal models
  • Define AI solution architectures that balance scalability, security, and cost
  • Produce technical blueprints, architecture diagrams, and deployment plans
  • Assess and recommend AI platforms, frameworks, and cloud services
  • Architect solutions with GPT, Claude, Gemini, Llama, Mistral, and other open-source LLMs
  • Develop strategies for prompt engineering, fine-tuning, and model optimization
  • Build retrieval-augmented generation pipelines with vector databases
  • Implement AI agents and orchestration frameworks
  • Design AI solutions across AWS, Azure, and Google Cloud
  • Create MLOps and LLMOps pipelines for deployment, monitoring, and governance
  • Design for high availability, scalability, and strong system performance
  • Translate business requirements into practical technical solutions
  • Lead client workshops, discovery sessions, and architecture reviews
  • Contribute to pre-sales work, RFP responses, demonstrations, and proposals
  • Present AI strategies and solution roadmaps to executives and other stakeholders
  • Establish responsible AI practices and governance frameworks
  • Address model security, privacy, compliance, and risk considerations
  • Define monitoring, observability, and evaluation frameworks for AI systems
  • Maintain alignment with enterprise architecture standards
  • Mentor and guide data scientists, ML engineers, and software teams
  • Review solution designs and implementation approaches
  • Track emerging Generative AI technologies and industry developments
  • Advance organizational innovation and AI adoption

Requirements

  • Bachelor’s or master’s degree in computer science, artificial intelligence, data science, or a related discipline
  • 8–15+ years of experience in software engineering, cloud architecture, or AI
  • 3–5+ years designing AI/ML solutions and architectures
  • Expertise in Generative AI, LLMs, RAG, and AI agents
  • Strong knowledge of machine learning and deep learning
  • Proficiency with Python, SQL, and REST APIs
  • Experience with LangChain, LangGraph, LlamaIndex, and CrewAI
  • Experience with Pinecone, Weaviate, Chroma, and Milvus vector databases
  • Experience across AWS, Azure, and GCP
  • Knowledge of Docker, Kubernetes, and CI/CD
  • Experience with MLOps and LLMOps
  • Understanding of data architecture and data engineering
  • Knowledge of AI security and governance
  • Strong solution design and architectural thinking
  • Effective client-facing communication
  • Stakeholder management experience
  • Leadership and mentoring capability
  • Strong problem-solving and decision-making skills
  • Presentation and consulting experience
  • Relevant certifications preferred, including AWS Solutions Architect, Azure AI Engineer or Azure Solutions Architect, Google Professional Cloud Architect, and Databricks or Snowflake certifications

Benefits

  • No specific benefits or additional compensation are provided

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