Senior AI Data Architect

Senior Data Architect (AI Solutions)

Location: Raleigh, NC (2 days per week in office) North Hills
Type: Full Time Position
Notes: Please review the MUST HAVE skills before applying

• Experience: 6–8 years in AI/ML engineering or architecture roles.
• Core Requirement: Built and scaled an AI platform end-to-end
  .
• Hands‑On: 70–80% coding
• Generative AI Expertise:
  • LLMs, Agentic AI, Retrieval-Augmented Generation (RAG).
    
    - MUST HAVE
  • Amazon Bedrock and related AWS AI services.
    
    - MUST HAVE
• Cloud: Strong AWS architecture and integration skills.
• Regulatory Exposure: Any regulated industry experience (finance, healthcare, pharma, etc.) preferred.
• Additional: Knowledge of vector databases, prompt engineering, and data governance.

The Senior Data Architect (AI Solutions) leads the design and implementation of cutting‑edge AI platforms and data systems. This role combines strong hands‑on engineering with strategic innovation to design, prototype, and deliver intelligent, data‑driven solutions that power analytics, machine learning, and next‑generation AI applications. This role collaborates closely with business and technology teams to turn ideas into working solutions, enabling faster insights, better decisions, and enterprise‑wide innovation through data.

• Prototype and operationalize advanced AI solutions, including GenAI and LLM-based systems.
• Build and integrate cloud-native data pipelines using tools such as Snowflake, Airflow, and Vertex AI.
• Implement retrieval‑augmented generation (RAG) pipelines and multimodal data solutions.
• Drive automation, observability, and performance optimization across AI and data workflows.
• Lead initiatives to explore, validate, and scale emerging AI technologies.
• Translate research and prototypes into production‑ready capabilities.
• Collaborate across teams to embed AI‑driven insights and automation into business processes.
• Evaluate and shape next‑generation AI trends, including agentic systems and autonomous workflows.
• Champion hands‑on experimentation and rapid solution delivery while maintaining technical excellence.
• Define and promote engineering standards that balance agility, scalability, and governance.
• Collaborate with security, compliance, and governance partners to ensure responsible data and AI usage.
• Mentor engineers and architects in modern data and AI development practices.
• Act as a trusted advisor for business and technology leaders on data‑driven innovation.
• Lead internal workshops and training sessions to accelerate AI adoption.
• Represent the organization in external forums, conferences, and publications focused on data and AI innovation.

• 10+ years of experience in enterprise data architecture or engineering, with a strong hands‑on focus on AI and cloud‑native data platforms.
• Proven experience in designing, implementing, and optimizing large‑scale AI systems, including LLM-based, GenAI, and agentic AI applications.
• Expertise in Python, SQL, and modern data frameworks (e.g., PySpark, Airflow, Snowflake, Lang Chain, Hugging Face, Vertex AI, OpenAI).
• Strong background in data modelling, distributed systems, and cloud architecture (AWS, GCP, or Azure).
• Experience developing and deploying AI/ML/GenAI pipelines leveraging vector databases and RAG frameworks.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.

• Experience with agentic AI design patterns, including tool‑use orchestration, autonomous workflow agents, or AI copilots.
• Proficiency in API design, microservices, and containerization (Docker, Kubernetes).
• Demonstrated ability to rapidly prototype new AI concepts and transition successful PoCs into production‑grade systems.