AI - Architect

Responsibilities

• Define and evolve reference architectures for AI, machine learning, and generative AI systems
• Establish technical standards, patterns, and best practices for scalable and secure AI development
• Guide platform decisions across data, model development, and deployment infrastructure
• Evaluate and recommend tools, frameworks, and vendors aligned with long-term architectural direction
• Develop end-to-end AI workflows for complex data interpretation, knowledge extraction, and reasoning
• Build systems that convert unstructured content into structured representations
• Develop and optimize retrieval approaches that combine semantic and lexical search techniques
• Prototype, evaluate approaches, test feasibility, and productionize generative AI solutions for real-world use cases
• Partner with engineering teams to develop technology infrastructure
• Optimize systems for latency, cost, and throughput
• Evaluate, reliability, and quality
• Design and implement evaluation approaches to assess performance, relevance, and effectiveness of AI solutions
• Apply techniques to improve consistency, accuracy, and trustworthiness of outputs
• Implement methods for scoring, explainability, and ongoing quality assurance
• Monitor deployed solutions and data pipelines for performance, stability, and data quality over time
• Incorporate responsible AI practices including transparency, bias mitigation, and risk controls
• Collaborate with cross-functional teams to align data science initiatives with business priorities
• Partner with leadership to identify and prioritize high-impact opportunities for data science applications
• Present insights and recommendations through clear visualizations tailored for audiences across different roles and expertise levels

Requirements

• Minimum 10+ years building AI, Machine Learning and NLP solutions
• Minimum 5+ years building applied AI/LLM and generative systems in production environments
• Bachelor’s degree in a relevant field such as Mathematics, Science, Engineering, or Computer Science. Master’s Degree in relevant discipline preferred
• Experience designing enterprise-scale AI and data architectures
• Experience with real-time and batch processing architectures
• Strong programming skills in Python and experience building data and AI pipelines
• Experience with information retrieval, semantic search, or knowledge-driven systems
• Experience with relational, non-relational, and semantic data stores
• Strong software engineering fundamentals (APIs, system design, testing, version control)
• Experience with Natural Language Processing methods and applications preferred

Qualifications

• Demonstrated initiative and ownership of tasks and projects
• Ability to prioritize, coordinate, and complete tasks to meet deadlines
• Ability to work effectively both independently and in team environments
• Ability to present complex problems in simple terms