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Llmops Jobs in Ohio (NOW HIRING)

Senior AI Engineer

Cleveland, OH · On-site +1

$101K - $139K/yr

You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless ...

Senior AI Engineer

Cleveland, OH · On-site

$101K - $139K/yr

You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless ...

... LLMOps pipelines and cloud AI platforms - Experience working in regulated environments (financial services preferred) - Strong understanding of AI governance, model risk, and data privacy

... LLMOps pipelines and cloud AI platforms - Experience working in regulated environments (financial services preferred) - Strong understanding of AI governance, model risk, and data privacy

Senior AI Engineer

Macedonia, OH · On-site

$120 - $150/hr

LLMOps/MLOps tooling and practices. Nice to have: * Broad / multi‑stack traditional software‑engineering background; * Experience with large, regulated organisations (banks, insurers, government ...

Senior AI Engineer

Toronto, OH · On-site

$93K - $128K/yr

... LLMOps tooling and platform design. • Experience designing platform‑level AI capabilities, not just individual models. Company : Scotiabank is a banking firm that provides banking and financial ...

AI & HPC Infrastructure Engineer

Cleveland, OH · On-site

$104K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Preferred Skills and Qualifications: * 2+ years of experience implementing MLOps, LLMOps, agentic AI, and DevSecOps frameworks to enable secure, automated, governed, and reproducible AI workflows ...

New

Deep, current subject matter expertise in modern AI architecture and engineering - LLMs, generative AI, agentic systems, classical ML, and the supporting MLOps/LLMOps tool ecosystem. * Proven ...

New

... LLMOps practices. * Establish monitoring and observability for model performance, drift, bias, fairness, hallucination, toxicity, safety, latency, cost, resilience, and overall system reliability.

... LLMOps practices. * Establish monitoring and observability for model performance, drift, bias, fairness, hallucination, toxicity, safety, latency, cost, resilience, and overall system reliability.

... LLMOps practices. * Establish monitoring and observability for model performance, drift, bias, fairness, hallucination, toxicity, safety, latency, cost, resilience, and overall system reliability.

AI & HPC Infrastructure Engineer

Hartford, OH · On-site

$96K - $126K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Preferred Skills and Qualifications: * 2+ years of experience implementing MLOps, LLMOps, agentic AI, and DevSecOps frameworks to enable secure, automated, governed, and reproducible AI workflows ...

New

... LLMOps practices. * Establish monitoring and observability for model performance, drift, bias, fairness, hallucination, toxicity, safety, latency, cost, resilience, and overall system reliability.

AI & HPC Infrastructure Engineer

Columbus, OH · On-site

$103K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Preferred Skills and Qualifications: * 2+ years of experience implementing MLOps, LLMOps, agentic AI, and DevSecOps frameworks to enable secure, automated, governed, and reproducible AI workflows ...

New

Enterprise Architect - AI

New Bremen, OH · On-site

$71.50 - $92.25/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Deep hands-on experience with AI/ML engineering, MLOps/LLMOps, and AI platform orchestration * Strong cloud, data, integration (API), and security architecture skills * Experience modeling ...

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Showing results 1-20

Llmops information

What is the difference between Llmops vs Data Scientist?

AspectLlmopsData Scientist
Required credentialsKnowledge of machine learning, AI frameworks, cloud platformsStatistics, programming, data analysis skills
Work environmentAI/ML teams, cloud environments, deployment pipelinesData analysis, modeling, reporting in various industries
Employer usageTech companies, AI startups, research labsFinance, healthcare, tech, retail

While both roles involve working with data and machine learning, Llmops focuses on deploying and maintaining large language models in production environments, requiring expertise in AI infrastructure. Data Scientists primarily analyze data, build models, and generate insights. Llmops professionals ensure models operate efficiently at scale, whereas Data Scientists develop the models and interpret results.

What are popular job titles related to Llmops jobs in Ohio?

For Llmops jobs in Ohio, the most frequently searched job titles are:

What cities in Ohio are hiring for Llmops jobs?

Cities in Ohio with the most Llmops job openings:

Infographic showing various Llmops job openings in Ohio as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 82% Physical, 8% Hybrid, and 10% Remote job distribution.

Senior Manager AI Architecture Innovation

Hexion, Inc.

OH • On-site, Remote

Full-time

Re-posted 25 days ago


Hexion rating

7.0

Company rating: 7.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

75th of 100 rated chemical manufacturers


Job description

Company Overview
Imagine Everything. Build the Future with Hexion.
At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress-developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.
This is where bold thinkers, problem-solvers, and innovators come together to shape what's next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.
We don't follow the status quo-we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger.
We invest in innovation, sustainability, and continuous development-equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.
Your Future Starts Here.
If you're ready to push limits, reimagine what's possible, and create the extraordinary, Hexion is where you belong.
Anything is possible when you imagine everything.
Position Overview
Define and own the enterprise GenAI platform strategy that makes every AI use case at Hexion possible. Build and operate reusable GenAI platform services - grounding, orchestration, memory, evaluation, and LLMOps - as production-grade shared infrastructure that accelerates delivery across Commercial, Supply Chain, R&D, and Manufacturing. Reports to Director, AI Architecture
This role is the engineering foundation of Hexion's AI transformation. The Senior Manager will build the GenAI platform layer that accelerates every use case across the enterprise - making safe, reliable, production-grade AI the default, not the exception
Job Responsibilities
Define and execute the enterprise GenAI technology strategy and platform roadmap, aligning capabilities to business priorities and measurable outcomes across all domains.
• Lead delivery of core GenAI platform services - retrieval/grounding, knowledge foundations, memory patterns, and agent orchestration - as reusable capabilities for teams across the enterprise.
• Partner with Data & Analytics to ensure AI-ready data foundations: governed access, data quality, lineage/metadata, indexing pipelines, and standardized measurement and telemetry.
• Establish LLMOps and AI quality standards: evaluation frameworks, release gates, drift monitoring, and lifecycle management for prompts and models to ensure consistent performance at scale.
• Embed security, privacy, Responsible AI, and compliance-by-design across all solutions through guardrails, risk reviews, auditability, and red-teaming practices.
• Own operational excellence and cost governance: reliability/SLOs, incident readiness, performance optimization, model routing/caching, and dashboards that manage latency and spend.
• Run AI Innovation portfolio, guide architecture and design for AI POVs, act as SME on make vs buy vs partner
Attributes
• Platform architect mindset - builds shared, reusable GenAI infrastructure that makes every product team faster rather than solving one-off problems.
• Engineering-first and delivery-oriented - pragmatic about what ships, not just what's architecturally elegant; known for enabling teams rather than gatekeeping them.
• Security and quality conscious - treats responsible AI, compliance-by-design, and operational reliability as core platform features, not afterthoughts.
• Collaborative and credible - earns trust from product teams, data scientists, security, and business leaders through technical depth and clear communication
Experience
• 10+ years of progressive software architecture and 3-5 years of AI/ML engineering experience; at least 3 years directly owning GenAI platform strategy, LLMOps, or enterprise AI infrastructure delivery.
• Demonstrated track record shipping GenAI or distributed AI systems at enterprise scale - from architecture and platform design through LLMOps, monitoring, and continuous improvement - with measurable reliability and performance outcomes.
• Experience building and leading engineering teams in transformation-stage enterprises; ideally with exposure to specialty chemicals, industrial manufacturing, or process industries and their AI/data integration patterns
Preferred Qualifications:
• Familiarity with AI security patterns: prompt injection defense, access controls, data governance, compliance-by-design, and cost governance for model routing and inference optimization. (Preferred)
• Specialty chemicals, industrial manufacturing, or process industry experience a plus - familiarity with IoT/sensor data, SAP AI extensions, and domain-specific AI use cases. (Preferred)
Knowledge, Skills, Attributes and Experience (KSAEs)
• 10+ years in software architecture, platform engineering, or 3-5 years AI/ML engineering; 3+ years leading GenAI or enterprise AI platform delivery at scale.
• Deep expertise in the Microsoft/Azure ecosystem: Azure OpenAI, AI Foundry, Cognitive Services, Semantic Kernel, and enterprise-scale cloud architecture patterns.
• Strong command of the full AI stack: experience surfaces, agentic orchestration (LangGraph, AutoGen, Semantic Kernel), knowledge/memory systems, model runtimes, evaluation frameworks, and infrastructure.
• Proven track record shipping AI-driven or distributed software systems at enterprise scale, with measurable reliability, performance, and cost outcomes.
• Strong understanding of hybrid AI architectures: local and cloud inference, model orchestration, multimodal runtimes, and RAG pipeline design.
• Expertise in LLMOps: evaluation frameworks, release gates, prompt/model lifecycle management, drift monitoring, and responsible AI guardrails including red-teaming and auditability.
• Hands-on proficiency with Azure AI Foundry, Azure OpenAI Service, Copilot Studio, and Microsoft Fabric; familiar with AKS/Kubernetes and CI/CD pipelines for AI workloads.
Other
We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.
To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.

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