Ai Tech Lead

Summary

Join Acryl Data as an AI Tech Lead and spearhead AI initiatives within DataHub, focusing on intelligent metadata management and AI infrastructure strategy. This role blends hands-on technical leadership in implementing AI-powered features with strategic planning for enterprise AI deployment. You will work at the intersection of data catalog systems and modern AI infrastructure, helping organizations navigate the complexities of enterprise AI deployment while ensuring robust governance and efficiency. Lead the technical implementation of AI features, architect scalable ML pipelines, and design systems for model monitoring. Shape the metadata framework for enterprise AI systems, define standards for managing AI-related metadata, and develop best practices for AI observability and governance. Provide technical leadership, mentor team members, and collaborate with product management and customers. Acryl Data offers a remote-first work environment and competitive benefits.

Requirements

• 8+ years of software engineering experience, with at least 4 years focused on ML/AI systems
• Strong experience with modern ML frameworks (PyTorch, TensorFlow) and MLOps tools
• Deep understanding of LLM deployment, fine-tuning, and operational considerations
• Experience with AI governance, including model monitoring, bias detection, and fairness metrics
• Strong background in data privacy and security, particularly in AI contexts
• Experience with enterprise AI deployment and infrastructure management
• Proficiency in Python and modern AI development tools
• Understanding of vector databases, embedding systems, and semantic search
• Experience with distributed systems and scalable architecture

Responsibilities

• Lead the technical implementation of AI-powered features in DataHub, including automated data classification, PII detection, and sensitive data identification
• Architect and implement scalable ML pipelines for continuous learning and model updates
• Design and implement systems for model monitoring, validation, and performance tracking
• Guide the team in implementing privacy-preserving ML techniques and ensuring compliance with data protection standards
• Shape the metadata framework needed to support enterprise AI systems, including model cards, lineage tracking, and deployment metadata
• Define standards for capturing and managing AI-related metadata, including training data versioning, model provenance, and deployment configurations
• Design systems to track and manage AI assets across the development lifecycle
• Develop best practices for AI observability and governance in enterprise settings
• Lead architectural decisions for AI systems integration within DataHub
• Mentor team members on ML engineering best practices and AI system design
• Collaborate with product management to define AI feature roadmap
• Work with customers to understand their AI infrastructure needs and challenges

Preferred Qualifications

• Experience working with DataHub is a huge plus!
• Experience building AI-powered features in enterprise SaaS products
• Background in data catalog or metadata management systems
• Familiarity with AI governance frameworks and standards
• Experience with AI infrastructure cost optimization
• Knowledge of regulatory requirements around AI systems
• Track record of building production ML systems

Benefits

• Salary Range: $235,000 to $300,000
• Equity
• 99% coverage of medical, dental and vision insurance for US Employees
• Carrot Fertility and Family Planning
• Remote friendly
• Monthly co-working salary
• One-time home office budget