Principal Data Scientist

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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