AI Architect

Role Overview

• 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
• Design and implement 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
• 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
• Work closely with cross functional team 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 Mathematics, Science, Engineering, or Computer Science
• 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
• Familiarity with data privacy considerations and AI
• Excellent analytical and problem solving skills
• 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

Tech Stack

• Python

Benefits

• Health insurance
• 401(k) matching
• Flexible work hours
• Paid time off
• Remote work options