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Metadata Library Jobs in New York (NOW HIRING)

IQVIA

Mgr, Database Management Systems

New York, NY

Organizes metadata for use by teams. Essential Functions Clinical Data Standards & Operational ... Global Library Management * Managing work assignments to ensure timely delivery of global library ...

Lancesoft

HR Coordinator

White Plains, NY · On-site

$28 - $32/hr

Basic understanding of library systems * Understanding taxonomy/metadata. * Experience with Content Server or other established records management systems. Education & Certifications * Bachelor ...

IQVIA

Mgr, Database Management Systems

Newark, NJ

Organizes metadata for use by teams. Essential Functions Clinical Data Standards & Operational ... Global Library Management * Managing work assignments to ensure timely delivery of global library ...

IQVIA

Mgr, Database Management Systems

Newark, NJ

Organizes metadata for use by teams. Essential Functions Clinical Data Standards & Operational ... Global Library Management * Managing work assignments to ensure timely delivery of global library ...

IQVIA

Mgr, Database Management Systems

New York, NY

Organizes metadata for use by teams. Essential Functions Clinical Data Standards & Operational ... Global Library Management * Managing work assignments to ensure timely delivery of global library ...

WWE

Content Operations Coordinator

Stamford, CT

Write and revise short-form titles, descriptions, and editorial metadata for new and library content. * Coordinate with Creative and Photo teams to request, track, revise, and deliver platform ...

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Metadata Library information

What are metadata librarians and what do they do?

Metadata librarians are information professionals who manage and organize metadata, which is data that describes other data, for library collections. They create, edit, and maintain metadata records to ensure resources are discoverable, accessible, and properly described in library catalogs and digital repositories. Their work supports searchability, digital preservation, and resource sharing by applying standards and best practices for cataloging. Metadata librarians often collaborate with IT staff, archivists, and subject specialists to enhance user access to library materials.

What is the difference between Metadata Library vs Metadata Specialist?

AspectMetadata LibraryMetadata Specialist
CredentialsTypically requires a degree in library science, information management, or related fieldsRequires similar credentials, often with additional certifications in data management or information systems
Work EnvironmentLibraries, archives, or information centers managing large metadata collectionsData-driven organizations, digital repositories, or information management teams
Employer & IndustryLibraries, museums, archives, academic institutionsTech companies, publishing, digital content providers
Search & Comparison IntentUnderstanding library metadata management rolesSpecialized data and metadata management tasks

The main difference is that a Metadata Library focuses on managing metadata within library and archival settings, while a Metadata Specialist handles metadata in broader digital and data environments. Both roles require similar credentials but serve different industry needs.

What are some common challenges faced by professionals working in a metadata library role, and how can they be addressed?

Professionals in a metadata library role often encounter challenges such as maintaining consistency and accuracy in metadata standards across diverse collections, keeping up with evolving cataloging guidelines, and integrating new technologies or platforms. Addressing these challenges typically involves ongoing training, collaboration with colleagues to develop clear metadata policies, and staying informed about industry best practices. Regular communication with IT teams and subject specialists is also key to ensuring that metadata effectively supports discoverability and access for library users.

What are the key skills and qualifications needed to thrive as a Metadata Librarian, and why are they important?

To thrive as a Metadata Librarian, you need expertise in cataloging standards (such as MARC, Dublin Core), metadata schema, and information organization, usually supported by a Master's in Library Science or a related field. Familiarity with integrated library systems (ILS), metadata management tools, and knowledge of cataloging software like OCLC Connexion is typical. Attention to detail, analytical thinking, and strong communication skills help ensure accuracy and facilitate collaboration with library staff. These skills and qualities are crucial to maintaining accessible, well-organized digital and print collections that support user discovery and research.
What are popular job titles related to Metadata Library jobs in New York? For Metadata Library jobs in New York, the most frequently searched job titles are:
What job categories do people searching Metadata Library jobs in New York look for? The top searched job categories for Metadata Library jobs in New York are:
What cities in New York are hiring for Metadata Library jobs? Cities in New York with the most Metadata Library job openings:
Metadata Library jobs near you
Infographic showing various Metadata Library job openings in New York as of July 2026, with employment types broken down into 1% Internship, 1% As Needed, 79% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.
Principal, AI Platform Engineering

Principal, AI Platform Engineering

Ares Management Corporation

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago

Job description

Over the last 20 years, Ares' success has been driven by our people and our culture. Today, our team is guided by our core values - Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy - and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.
Job Description
Overview
We are seeking an exceptional Principal AI Platform Engineer to design and build an enterprise-grade generative AI platform from the ground up. This is a leadership role that combines deep technical expertise in AI systems architecture with the strategic vision to shape how our organization scales AI capabilities across all business domains. You will architect a comprehensive platform spanning model gateways, retrieval services, model registries, prompt libraries, and deployment pipelines-enabling teams across the firm to build, deploy, and operationalize AI applications with confidence, compliance, and security.
Key Responsibilities
Platform Architecture & Design
  • Design and build a foundational AI platform that enables secure, scalable, and compliant generative AI across the enterprise
  • Architect multi-LLM gateway capabilities to support diverse model providers, allowing teams to leverage best-of-breed models for different use cases
  • Establish platform standards and patterns that balance flexibility, safety, governance, and performance

Core Platform Components
  • Develop multi-LLM gateway: unified interface for accessing multiple LLM providers with load balancing, fallback handling, and cost optimization
  • Build RAG (Retrieval-Augmented Generation) retrieval services: enterprise search, semantic indexing, and document retrieval at scale
  • Create model registry and governance: centralized catalog of models, versions, fine-tuning metadata, performance metrics, and compliance tracking
  • Design prompt library and version control: organizational repository for prompts with testing, evaluation, and A/B testing capabilities
  • Implement Model Context Protocol (MCP) gateway: enable secure integration between AI applications and external tools, APIs, and data sources
  • Build FinOps infrastructure: cost tracking, optimization, and allocation across models, usage patterns, and business units

Agent-to-Agent (A2A) Workflows
  • Design orchestration framework for complex, multi-step AI workflows across applications
  • Enable reliable, scalable execution of chained AI operations with state management and error recovery
  • Integrate with broader data ecosystem for workflow triggers and data pipelines

Data Gateway Integration
  • Partner with data platform teams to design AI-native data access patterns
  • Enable secure, governed access to enterprise data and RAG and model training
  • Build metadata and lineage tracking for AI-consumed data

Deployment & DevOps
  • Design sandbox-to-production pipelines: safe, repeatable processes for testing and deploying AI applications
  • Implement CI/CD for AI models: versioning, testing, promotion, and rollback capabilities
  • Build observability and monitoring: telemetry, performance metrics, cost tracking, and compliance auditing
  • Establish disaster recovery and high-availability patterns

Collaboration & Enablement
  • Work closely with Data Products team to align platform capabilities with data governance and analytics infrastructure
  • Partner with AI Enablement teams to provide tools, SDKs, documentation, and best practices that democratize AI development
  • Lead technical discussions on platform strategy, roadmap, and trade-offs across the organization
  • Build internal developer experience and platform adoption

Security Architecture & Implementation
  • Design and implement comprehensive security architecture aligned with firm cyber and information security guidelines
  • Build authentication and authorization frameworks: role-based access control (RBAC), attribute-based access control (ABAC), and service-to-service authentication
  • Implement encryption standards: encryption at rest (AES-256 or equivalent) and in transit (TLS 1.2+) for all sensitive data
  • Design secure API gateways and service boundaries with rate limiting, request validation, and DDoS protection
  • Implement secrets management: secure storage and rotation of credentials, API keys, and certificates
  • Build comprehensive audit logging and monitoring: all access, modifications, and security events logged with immutable audit trails
  • Partner with Infosec and Security Operations to implement continuous security monitoring and threat detection

Governance, Compliance & Risk Management
  • Ensure platform compliance with regulatory requirements: SOC 2 Type II, data residency, and audit trails
  • Implement data governance: classify data sensitivity levels, enforce data handling policies, and ensure appropriate access controls
  • Build model governance: track model provenance, versioning, training data lineage, and approval workflows for production deployment
  • Prevent data exfiltration and prompt injection attacks through input validation, output filtering, and rate limiting
  • Establish responsible AI practices: bias detection, fairness assessment, and explainability requirements
  • Manage third-party vendor security: assess LLM provider security postures, data processing agreements, and compliance certifications
  • Create model risk assessment framework: evaluate models for regulatory, market, and operational risks before production deployment
  • Work with Compliance, Legal, and Risk teams to ensure platform meets all governance requirements and documentation standards

Required Qualifications
  • 10+ years of software engineering experience, with 5+ years building large-scale, distributed systems or platform infrastructure
  • 3+ years of hands-on experience with generative AI, LLMs, RAG systems, or AI infrastructure-either in production systems or applied research
  • Deep expertise in one or more: Python, Go, Rust, or Java; experience building APIs and orchestration systems
  • Strong understanding of LLM architectures, prompting strategies, fine-tuning, and RAG design patterns
  • Demonstrated experience with: model serving (vLLM, Ollama, TensorFlow Serving), vector databases, and embedding models
  • Proficiency in cloud platforms (AWS, GCP, Azure) and containerization/orchestration (Docker, Kubernetes)
  • Experience designing and building multi-tenant, secure platform systems with strong governance and observability
  • Demonstrated expertise in security: architecture, secure coding practices, authentication/authorization, encryption, and threat modeling
  • Experience with compliance frameworks and security certifications: SOC 2, ISO 27001, GDPR, or similar
  • Track record of leading technical initiatives from architecture through production deployment
  • Excellent communication skills; ability to explain complex technical and security concepts to executives and cross-functional teams

Preferred Qualifications
  • Experience in financial services, private equity, or alternative assets technology environments
  • Familiarity with LangChain, LlamaIndex, or similar AI orchestration frameworks
  • Experience with MLOps tools and practices: model versioning, feature stores, experiment tracking
  • Knowledge of eval frameworks, retrieval evaluation, or AI model benchmarking
  • Experience with data governance platforms or metadata management systems
  • Experience building zero-trust architectures or implementing security controls in cloud-native environments
  • Contributions to open-source AI/ML projects or publications in the AI/ML space
  • Experience in building developer platforms or internal tools that drive organizational adoption

Reporting Relationships
Partner, Chief Information Officer
Compensation
The anticipated base salary range for this position is listed below. Total compensation may also include a discretionary performance-based bonus. Note, the range takes into account a broad spectrum of qualifications, including, but not limited to, years of relevant work experience, education, and other relevant qualifications specific to the role.
$300,000 - $350,000
The firm also offers robust Benefits offerings. Ares U.S. Core Benefits include Comprehensive Medical/Rx, Dental and Vision plans; 401(k) program with company match; Flexible Savings Accounts (FSA); Healthcare Savings Accounts (HSA) with company contribution; Basic and Voluntary Life Insurance; Long-Term Disability (LTD) and Short-Term Disability (STD) insurance; Employee Assistance Program (EAP), and Commuter Benefits plan for parking and transit.
Ares offers a number of additional benefits including access to a world-class medical advisory team, a mental health app that includes coaching, therapy and psychiatry, a mindfulness and wellbeing app, financial wellness benefit that includes access to a financial advisor, new parent leave, reproductive and adoption assistance, emergency backup care, matching gift program, education sponsorship program, and much more.
There is no set deadline to apply for this job opportunity. Applications will be accepted on an ongoing basis until the search is no longer active.

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