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Metadata Librarian Jobs in Michigan (NOW HIRING)

Build the MCP Integration Layer • Implement MCP server and client libraries that connect ... embedding generation, metadata enrichment, and upsert into vector stores • Build retrieval ...

New

... metadata, and lifecycle status are maintained. - Develop and maintain responsible AI templates ... domain-specific guardrail libraries; standardize governance artifacts; define end-user ...

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

GCP Data Engineer

Dearborn, MI · On-site

$61 - $66/hr

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

Establish enterprise standards for metadata, including tagging, classification, lineage, and ... Understanding of statistical analysis, data modeling, and ML libraries. Education Required

$94K - $124K/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 ...

New

Senior, ML Engineer - Auto Tagging

Ann Arbor, MI · On-site +1

$102K - $140K/yr

... curated library of critical driving scenarios. By mining driving logs for long-tail events, we ... metadata integrity. * Data Flywheel Integration: Manage the ingestion of tagged events into the ...

Senior, ML Engineer - Auto Tagging

Ann Arbor, MI · On-site +1

$102K - $140K/yr

... curated library of critical driving scenarios. By mining driving logs for long-tail events, we ... metadata integrity. * Data Flywheel Integration: Manage the ingestion of tagged events into the ...

Showing results 21-37

Metadata Librarian information

See Michigan salary details

$22.7K

$54.1K

$87.6K

How much do metadata librarian jobs pay per year?

As of Aug 22, 2026, the average yearly pay for metadata librarian in Michigan is $54,088.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,100.00 and $63,200.00 per year, depending on experience, location, and employer.

What does a metadata librarian do?

A Metadata Librarian is responsible for creating, managing, and organizing metadata to ensure efficient access to library resources. They apply metadata standards, schemas, and controlled vocabularies to describe digital and physical materials, enhancing discoverability. They often work with cataloging systems, digital repositories, and database technologies to support scholarly research and user access. Additionally, they collaborate with colleagues to develop metadata policies and workflows that align with institutional and industry best practices. Their role is essential in improving resource organization, retrieval, and long-term digital preservation.

What are some typical daily responsibilities of a metadata librarian?

A Metadata Librarian typically spends each day creating, reviewing, and maintaining metadata for library resources such as books, digital collections, and special archives to ensure accurate organization and discoverability. This includes applying established metadata standards, collaborating with colleagues to enhance workflows, and troubleshooting any metadata quality issues. You may also participate in projects to improve metadata practices, support digital initiatives, and train staff on new processes or systems. The role often involves working closely with catalogers, digital librarians, and IT teams to support the library's mission and resource accessibility.

What are the key skills and qualifications needed to thrive in the metadata librarian position, and why are they important?

To thrive as a Metadata Librarian, you need a strong understanding of metadata standards, cataloging principles, and information organization, typically supported by a degree in library and information science or a related field. Familiarity with integrated library systems (ILS), metadata schema like MARC, Dublin Core, or MODS, and tools such as OCLC or CONTENTdm is essential. Strong analytical skills, attention to detail, and effective communication help Metadata Librarians collaborate and solve problems efficiently. These competencies are crucial for ensuring accurate resource description, efficient information retrieval, and consistent library data management.

What are the most commonly searched types of Metadata Librarian jobs in Michigan?

The most popular types of Metadata Librarian jobs in Michigan are:

What are popular job titles related to Metadata Librarian jobs in Michigan?

For Metadata Librarian jobs in Michigan, the most frequently searched job titles are:

What cities in Michigan are hiring for Metadata Librarian jobs?

Cities in Michigan with the most Metadata Librarian job openings:

Infographic showing various Metadata Librarian job openings in Michigan as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution, with an average salary of $54,088 per year, or $26 per hour.

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


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.

IT Software Engineer, Core AI Development

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 IT Software Engineer in the Orchestration AI Development team, you will move beyond using AI tools, you will build them.

You will implement the foundational components of NICE's AI architecture: the integration layer that connects enterprise systems via MCP, the agent orchestration engine, the Models Gateway, RAG pipelines, and the tooling that makes every developer at NICE more productive. Your work ships to production and is used daily by hundreds of colleagues.

This is a full-stack engineering role with a strong AI focus. You will write clean, production-quality code, collaborate closely with the Software Architect and DevOps teams, and operate with significant autonomy on technically complex problems.

 How will you make an impact?  

You will own and build the core components of NICE's AI platform, the integration layer, agent platform, Models Gateway, RAG pipelines, and developer tooling, working hands-on across the stack with the Architect, DevOps, and Security teams.

Build the MCP Integration Layer

• Implement MCP server and client libraries that connect enterprise systems (Atlassian, Microsoft 365, ServiceNow, Workday, Salesforce, Snowflake) to AI agents

• Design and expose clean tool schemas; handle auth flows (OAuth2, managed identity); implement error handling, retries, and rate limiting

• Build the A2A (Agent-to-Agent) interoperability layer enabling multi-agent collaboration across the platform

Develop the AI Agentic Platform

• Implement production-grade AI agent frameworks: ReAct loops, tool-augmented reasoning, multi-agent orchestration, memory and state management

• Build agent harnesses for specific NICE use cases: IT helpdesk automation, procurement workflows, HR self-service, developer productivity agents

• Integrate with Azure AI Foundry and Anthropic Claude API, managing context windows, tool use, streaming responses, and multi-turn conversations

Engineer the Models Gateway

• Build a unified gateway abstracting multiple LLM providers (Azure OpenAI, Anthropic, open-source models via Azure ML)

• Implement model routing logic, fallback chains, cost-based dispatch, latency budgeting, and per-team quota enforcement

• Add logging, token metering, and usage dashboards for FinOps visibility

Build RAG Pipelines & Vector Infrastructure

• Design and implement document ingestion pipelines: chunking, embedding generation, metadata enrichment, and upsert into vector stores

• Build retrieval pipelines with hybrid search (dense + sparse), re-ranking, and context assembly for LLM prompts

• Manage vector DB infrastructure on Azure AI Search and /other ; own schema design and index optimization

Implement Prompt Management & LLM Evals

• Build a prompt registry: version control, templating engine, environment promotion, and rollback

• Design and run LLM evaluation pipelines: automated regression tests, hallucination detection, task-specific benchmarks

• Implement human-in-the-loop feedback collection and model performance tracking dashboards

Contribute to Developer Tooling & CI/CD

• Build and maintain GitHub Actions workflows for AI component testing, deployment, and rollback

• Write reusable SDK / client libraries for internal teams consuming the AI platform

• Integrate GitHub Copilot and Azure AI Foundry into the development workflow; document patterns for the broader R&D org

Observability & Production Operations

• Instrument all AI components with OpenTelemetry: traces, metrics, and structured logs

• Build Azure Monitor dashboards and alerts covering inference latency, error rates, token spend, and agent success rates

• Participate in on-call rotation for critical AI platform services

Have you got what it takes?

• 2-5 years of professional software engineering experience with Python or TypeScript in production environments

• Hands-on experience building and deploying LLM-powered applications: RAG pipelines, agents, tool use, or prompt engineering systems

• Strong understanding of REST API design, async programming, and event-driven architecture

• Experience with at least one agent or orchestration framework: LangChain, LangGraph, AutoGen, CrewAI, or equivalent

• Practical knowledge of Azure services : at minimum Azure OpenAI, Azure Storage, and Azure Container Apps or AKS

• Solid Git workflow: branching, PRs, code review, CI integration

• Ability to write clean, tested, documented code that others can build on

• Comfort working in fast-moving environments with evolving requirements

• Fluency in English

Bonus: 

• Experience implementing MCP servers / clients or similar tool-integration protocols

• Familiarity with the Anthropic Claude API, tool use patterns, and multi-turn conversation management

• Experience with vector databases: Azure AI Search, pgvector, Qdrant, Weaviate, or Pinecone

• Knowledge of LLM evaluation frameworks: Evals, RAGAS, LangSmith, or custom harness development

• Experience with GitHub Copilot enterprise configuration, policy management, or extension development

• Background in enterprise IT systems integration (Jira, ServiceNow, Salesforce, Workday, M365)

• Familiarity with OpenTelemetry instrumentation and Azure Monitor / Grafana

Why Join Us? 

At NiCE, we don’t just connect systems , we connect people, platforms, and possibilities. In this role, you’ll be at the heart of driving product unification, governance, and go-to-market alignment across a mission-critical platform. You’ll join a team that breaks down silos and enables seamless customer experiences across our product ecosystem. 

If you are a strategic thinker, a collaborative leader, and passionate about delivering cross-platform value, this is your opportunity to shape the future of customer experience 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!

Enjoy NiCE-FLEX!

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

NICE Ltd. (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 crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ 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.