AI Tech Lead, Bay Area Hybrid at DataHub

Palo Alto, California, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Jun, 26

Salary

0.0

Posted On

22 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Features Implementation, ML Pipelines, Model Monitoring, Privacy-Preserving ML, AI Infrastructure Strategy, Metadata Framework, AI Observability, Technical Leadership, Architectural Decisions, PyTorch, TensorFlow, LLM Deployment, AI Governance, Python, Vector Databases, Distributed Systems

Industry

Software Development

Description

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. Key Responsibilities AI Features & Implementation 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 AI Infrastructure Strategy 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 Technical Leadership 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 Required Qualifications 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 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 Essential Knowledge Areas Deep understanding of enterprise AI infrastructure components Model serving platforms Vector databases Training infrastructure Feature stores Model monitoring systems AI governance tools Familiarity with key considerations for enterprise AI deployment Cost optimization strategies Security requirements Compliance considerations Performance monitoring Resource management Model versioning and rollback strategies If you're passionate about technology, enjoy working with customers, and want to be part of a fast-growing company changing the industry, we want to hear from you! This is a hybrid role with the expectation the employee will travel to the office a few times a week during the first few months of employment, and will continue to come to the office in Palo Alto on a regular basis. Benefits and Perks We invest in people so they can do their best work and enjoy doing it. Our benefits reflect the way we build: practical, thoughtful, and designed to support long-term growth. Competitive compensation We offer salaries that reflect your skills, experience, and the impact you make. You bring value—we make sure you're recognized for it. Equity for everyone Every team member receives an ownership stake in the company. When we grow, you grow with us. Remote Work All roles are remote unless otherwise specified in the job description. Review the job description to confirm if the role you are interested in is remote or hybrid. Location flexibility Home office, coworking space, or something in between? We support your ideal setup. You’ll receive a monthly coworking stipend to use whenever you need a change of pace or in-person collaboration time. Comprehensive health coverage Your well-being matters. We cover 99% of medical, dental, and vision premiums employees, and 65% for dependents. Flexible savings accounts We offer FSAs to help cover planned or unexpected healthcare costs. You can also opt into a Dependent Care FSA to support family needs. Support for every path to parenthood Through Carrot Fertility, we provide inclusive fertility benefits and family-forming support. All U.S. employees have access, regardless of age, gender identity, or family structure. Time off that works for you We trust you to take the time you need. Our unlimited PTO and sick leave policy is designed for flexibility, rest, and real life. Why Join Us DataHub is at a rare inflection point: we’ve achieved product-market fit, earned the trust of leading enterprises, and secured backing from top-tier investors like Bessemer Venture Partners and 8VC. The context platform market is expected to grow from $1B to $9B in the next five years—and we’re leading the way. By joining our team, you’ll: Tackle high-impact challenges at the heart of enterprise AI infrastructure Ship production systems that power real-world use cases at global scale Collaborate with a high-caliber team of builders who’ve scaled some of the most influential data tools in the world Build the next generation of AI-native data systems, including conversational agents, intelligent classification, automated governance, and more If you're passionate about technology, enjoy working with customers, and want to be part of a fast-growing company changing the industry, we want to hear from you!

Responsibilities

The AI Tech Lead will spearhead AI initiatives focusing on intelligent metadata management, leading the technical implementation of AI features like automated data classification and architecting scalable ML pipelines. This role also involves shaping the AI infrastructure strategy, defining standards for AI-related metadata, and designing systems for AI observability and governance.