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Metadata Library Jobs in Newnan, GA (NOW HIRING)

Team Lead, AI Engineering

Atlanta, GA · On-site

$140 - $220/hr

Guide implementation of MCP server and client libraries that connect enterprise systems to AI ... Oversee RAG pipeline design, including ingestion, chunking, embedding generation, metadata ...

Sharepoint Engineer

Atlanta, GA · On-site

$120 - $150/hr

Build, configure, deploy, and maintain SharePoint Online sites, hubs, document libraries, lists, pages, navigation structures, content types, and metadata * Design and implement scalable SharePoint ...

Sharepoint Engineer

Atlanta, GA · On-site

$110 - $160/hr

Build, configure, deploy, and maintain SharePoint Online sites, hubs, document libraries, lists, pages, navigation structures, content types, and metadata * Design and implement scalable SharePoint ...

Team Lead, AI Engineering

Atlanta, GA · On-site

$98K - $129K/yr

... libraries that connect enterprise systems to AI agents, including Atlassian, Microsoft 365 ... generation, metadata enrichment, hybrid search, re-ranking, context assembly, and vector index ...

Showing results 21-26

Metadata Library information

See Newnan, GA salary details

$8

$16

$24

How much do metadata library jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for metadata library in Newnan, GA is $16.86, according to ZipRecruiter salary data. Most workers in this role earn between $13.65 and $19.09 per hour, depending on experience, location, and employer.

What is a metadata librarian?

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 skills and qualifications are needed to thrive as a metadata librarian?

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 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 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 popular job titles related to Metadata Library jobs in Newnan, GA?

For Metadata Library jobs in Newnan, GA, the most frequently searched job titles are:

What job categories do people searching Metadata Library jobs in Newnan, GA look for?

The top searched job categories for Metadata Library jobs in Newnan, GA are:

What cities near Newnan, GA are hiring for Metadata Library jobs?

Cities near Newnan, GA with the most Metadata Library job openings:

Team Lead, AI Engineering

Nice-0a1ef543

Atlanta, GA • On-site

$140 - $220/hr

Other

Posted 5 days ago


Key responsibilities

  • Lead the engineering roadmap and delivery execution for core AI platform capabilities, ensuring priorities are clear, sequenced, and aligned to business outcomes

  • Lead, mentor, and grow engineers working across AI platform, full‑stack development, integration, orchestration, evaluation, and production operations

  • Guide implementation of MCP server and client libraries, lead delivery of agent orchestration capabilities, and oversee development of Models Gateway, RAG pipelines, prompt management, and evaluation systems


Job description

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.

Team Lead, AI Engineering

So, what’s the role all about?

NICE is assembling a core engineering team to build the internal AI platform that powers intelligent automation across the enterprise. As Team Lead, AI Engineering in the Orchestration AI Development team, you will lead a hands‑on engineering team responsible for building the foundational AI platform capabilities that enable teams across NICE to move faster, automate intelligently, and deliver measurable business impact.

You will guide the design, delivery, and production readiness of NICE's AI architecture , including the MCP integration layer , agent orchestration engine, Models Gateway, RAG pipelines, prompt management, LLM evaluation, and developer tooling. This role requires both technical depth and people leadership: you will set engineering direction, coach engineers, remove delivery barriers, and ensure platform capabilities are scalable, secure, observable, and adopted by internal teams.

This is a leadership role for a builder who remains close to the technology . You will partner closely with the Software Architect, DevOps, Security, Product, and business stakeholders to translate complex enterprise needs into reliable AI platform capabilities while growing a high‑performing engineering team.

How will you make an impact?

You will lead the team that builds and scales the core components of NICE's AI platform, including the integration layer, agent platform, Models Gateway, RAG pipelines, prompt and evaluation systems, and developer tooling.

  • Lead the engineering roadmap and delivery execution for core AI platform capabilities, ensuring priorities are clear, sequenced, and aligned to business outcomes
  • Partner with architecture, DevOps, Security, Product, and business stakeholders to translate complex requirements into scalable technical plans
  • Own delivery quality across releases, including code review standards, test coverage, production readiness, operational runbooks, and rollback plans

Build and Develop a High‑Performing AI Engineering Team

  • Lead, mentor, and grow engineers working across AI platform, full‑stack development, integration, orchestration, evaluation, and production operations
  • Create a strong engineering culture focused on ownership, technical excellence, learning, collaboration, and pragmatic delivery
  • Coach team members through technical decisions, design reviews, incident learnings, and career development while maintaining high standards for execution

Guide Core AI Platform Architecture and Execution

  • Guide implementation of MCP server and client libraries that connect enterprise systems to AI agents, including Atlassian, Microsoft 365, ServiceNow, Workday, Salesforce, and Snowflake
  • Lead delivery of agent orchestration capabilities, including ReAct loops, tool‑augmented reasoning, multi‑agent workflows, memory, state management, and A2A interoperability
  • Ensure technical designs address security, authentication, reliability, performance, observability, and long‑term maintainability

Scale Models Gateway, RAG, and Evaluation Capabilities

  • Lead development of the Models Gateway, including provider abstraction, model routing, fallback chains, cost‑based dispatch, latency budgeting, quota enforcement, and FinOps visibility
  • Oversee RAG pipeline design, including ingestion, chunking, embedding generation, metadata enrichment, hybrid search, re‑ranking, context assembly, and vector index optimization
  • Establish standards for prompt management, version control, environment promotion, rollback, LLM evaluation, regression testing, hallucination detection, and human‑in‑the‑loop feedback

Drive Adoption, Governance, and Cross‑Functional Impact

  • Partner with internal teams to identify high‑value AI use cases and convert them into reusable platform capabilities, SDKs, patterns, and documentation
  • Define governance practices that support responsible AI development, secure enterprise integration, cost transparency, and compliant use of internal data
  • Measure platform adoption, reliability, developer productivity, operational efficiency, and business impact through clear dashboards and success metrics

Ensure Production Excellence and Continuous Improvement

Have you got what it takes?

  • 7+ years of professional software engineering experience, including hands‑on experience with Python, TypeScript, or similar languages in production environments
  • 2+ years of technical leadership, team leadership, or engineering management experience, with a track record of mentoring engineers and driving delivery outcomes
  • Hands‑on experience building and deploying LLM‑powered applications, including RAG pipelines, agents, tool use, prompt engineering systems, or evaluation frameworks
  • Strong understanding of REST API design, async programming, distributed systems, event‑driven architecture, and production engineering practices
  • Experience with at least one agent or orchestration framework such as LangChain, LangGraph, AutoGen, CrewAI, or equivalent
  • Demonstrated ability to set engineering standards for code quality, testing, documentation, security, observability, and CI/CD
  • Strong communication and stakeholder management skills, with the ability to translate technical complexity into clear business impact
  • Ability to lead through ambiguity, prioritize effectively, and keep teams aligned in a fast‑moving environment with evolving requirements

Bonus:

  • Experience implementing MCP servers, clients, or similar tool‑integration protocols at enterprise scale
  • Familiarity with Anthropic Claude API, Azure AI Foundry, Azure OpenAI, tool use patterns, and multi‑turn conversation management
  • Experience with vector databases such as Azure AI Search, pgvector, Qdrant, Weaviate, or Pinecone
  • Knowledge of LLM evaluation frameworks such as Evals, RAGAS, LangSmith, or custom harness development
  • Experience leading developer platform, internal tools, AI platform, or infrastructure engineering teams
  • Background in enterprise IT systems integration, including Jira, ServiceNow, Salesforce, Workday, Microsoft 365, or Snowflake
  • Familiarity with OpenTelemetry instrumentation, Azure Monitor, Grafana, FinOps, and production reliability practices

Why Join Us?

At NiCE , we don’t just connect systems, we connect people, platforms, and possibilities. In this role, you’ll lead a team at the center of NiCE’s internal AI transformation, building the platform foundations that help teams automate work, improve developer productivity, and scale AI responsibly across the enterprise.

If you are a technical leader, hands‑on builder, and collaborative people manager who is excited to shape how AI is engineered, governed, and adopted at enterprise scale, this is your opportunity to build the future of work with NiCE .

What’s in it for you?

Join an ever‑growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast‑paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

At NiCE, we work according to the NiCE‑FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face‑to‑face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

About NiCE

NICELtd. (NASDAQ: NICE)software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences,fight financial crimeand ensure public safety.Every day, NiCE software managesmore than120 million customer interactions and monitors3+billion financial transactions.

Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.

NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.

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