AI Tech Lead, Bay Area Hybrid

DataHub•Palo Alto, CA

7d•Hybrid

About The Position

DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities. Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos. AI Tech Lead, San Francisco Bay Area Role Overview We're seeking an experienced AI Technical Lead to spearhead our AI initiatives within DataHub, focusing on intelligent metadata management and shaping our AI infrastructure strategy. This role combines hands-on technical leadership in implementing AI-powered features with strategic thinking about how enterprises deploy and manage AI systems at scale. You'll 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.

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

Nice To Haves

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

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