Data Architect

Job Purpose

Contract Terms

• This is a definite-term contract for three years.

AI and Data Architecture

• Evaluate, test, and design end-to-end data and AI architectures from proof of concept through production deployment.
• Architect enterprise data platforms for AI, ML, LLM integration, and inference at scale.
• Define patterns for fine-tuning, retrieval-augmented generation, prompt engineering, multimodel environments, and autonomous agents.
• Design semantic layers, indexing, similarity search, knowledge graphs, and retrieval observability mechanisms.
• Assess AI models, platforms, and tools using defined evaluation criteria and benchmarking.

Data Integration and MLOps

• Provide guidance for data integration and ingestion across enterprise platforms in alignment with data modelling and MDM standards.
• Define batch, streaming, real-time, medallion, Kappa, and Lambda architecture patterns.
• Document reference architectures and standard solution patterns, including design documents, data models, dictionaries, dashboards, and reports.
• Design pipelines and CI/CD flows for model training, evaluation, deployment, and retraining with monitoring for accuracy, latency, and cost.

Governance and Architecture Review

• Align solutions with data and AI governance, information security controls, enterprise architecture, and PMO standards.
• Design privacy-preserving architectures and support security controls and access patterns for data and AI platforms.
• Support Architecture Review Board and Design Advisory sessions for data, AI, and ML solution reviews.
• Provide structured feedback and technical guidance to delivery, operations, governance, and related teams.

Education and Experience

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant field.
• Specialization or certification in AI, ML engineering, or data science.
• At least 8 years of relevant experience in technical AI implementation and data architecture.
• Experience with machine learning, deep learning, NLP, computer vision, and text analytics.
• Hands-on experience with data agents, operational agents, and agentic AI.
• A track record of delivering successful AI or data digital products in industry.

Job-Specific Skills

• Strong AI-ready data platform, data architecture, data engineering, and AI implementation skills.
• Strong AI and ML architecture expertise, including agentic and autonomous AI and the MLOps lifecycle.
• Experience with software development lifecycle, DevOps practices, and CI/CD model pipelines.
• Experience with agile tools such as Jira, Confluence, or similar is required.
• Experience with OSDU or Cognite Data Fusion is a plus.