Principal Data Scientist

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Brief about Fractal

Fractal Analytics is Leading Fortune 500 companies leverage Big Data, Analytics and technology to drive smarter, faster and more accurate decisions in every aspect of their business.

Fortune 500 companies recognize analytics is a competitive advantage to understand customers and make better decisions. We deliver insight, innovation and impact to them through predictive analytics and visual story-telling.

The Artificial Intelligence and Machine Learning (AIML) group at Fractal Analytics is actively involved in helping Fortune 500 companies by enabling them to discover how they can leverage their data using advanced and sophisticated AI/ML algorithms for which we are looking for Data Scientists with the capability to work on independent statistical and machine learning research/ projects. If you are a problem solver with a curiosity for exploring new techniques and technologies in AIML space, then we would like to talk with you.

Position Summary

We are seeking an experienced Gen AI Solution Architect to design and deliver scalable, secure, and business-focused Generative AI solutions. The ideal candidate will combine deep expertise in AI/ML technologies with strong architecture, cloud, and stakeholder management skills to drive AI transformation initiatives.

Key Responsibilities

Solution Architecture & Design

• Design end-to-end Generative AI architectures using LLMs, RAG, AI Agents, vector databases, and multimodal models.
• Define scalable, secure, and cost-effective AI solution architectures.
• Create technical blueprints, architecture diagrams, and deployment strategies.
• Evaluate and recommend AI platforms, frameworks, and cloud services.

AI & LLM Engineering

• Architect solutions using models such as GPT, Claude, Gemini, Llama, Mistral, and open-source LLMs.
• Design prompt engineering, fine-tuning, and model optimization strategies.
• Build RAG pipelines using vector databases such as Pinecone, Weaviate, Chroma, or Azure AI Search.
• Implement AI agents and orchestration frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.

Cloud & Platform Architecture

• Design AI solutions on AWS, Azure, or Google Cloud.
• Utilize services such as Azure OpenAI, AWS Bedrock, Vertex AI, and AI Foundry.
• Architect MLOps and LLMOps pipelines for deployment, monitoring, and governance.
• Ensure high availability, scalability, and performance.

Business & Stakeholder Engagement

• Gather business requirements and translate them into technical solutions.
• Conduct client workshops, discovery sessions, and architecture reviews.
• Support pre-sales activities, RFP responses, solution demonstrations, and proposal creation.
• Present AI strategies and solution roadmaps to executives and stakeholders.

Governance, Security & Compliance

• Establish responsible AI practices and governance frameworks.
• Address model security, privacy, compliance, and risk management.
• Define monitoring, observability, and evaluation frameworks for AI systems.
• Ensure alignment with enterprise architecture standards.

Leadership & Mentorship

• Guide data scientists, ML engineers, and software development teams.
• Review solution designs and implementation approaches.
• Stay current with emerging Gen AI technologies and industry trends.
• Drive innovation and AI adoption across the organization.

Required Skills

Technical Skills

• Generative AI, LLMs, RAG, AI Agents
• Machine Learning and Deep Learning
• Python, SQL, REST APIs
• LangChain, LangGraph, LlamaIndex, CrewAI
• Vector Databases (Pinecone, Weaviate, Chroma, Milvus)
• AWS, Azure, GCP
• Docker, Kubernetes, CI/CD
• MLOps / LLMOps
• Data Architecture and Data Engineering
• AI Security and Governance

Soft Skills

• Solution design and architecture thinking
• Client-facing communication
• Stakeholder management
• Leadership and mentoring
• Problem-solving and decision-making
• Presentation and consulting skills

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 8–15+ years of software engineering, cloud architecture, or AI experience.
• 3–5+ years of experience in AI/ML solution architecture.
• Relevant certifications preferred:
• AWS Solutions Architect
• Azure AI Engineer / Azure Solutions Architect
• Google Professional Cloud Architect
• Databricks or Snowflake certifications

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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