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Professional Llm Developer Jobs in Ohio (NOW HIRING)

Senior Application Security Engineer

Independence, OH · Hybrid

$111K - $153K/yr

CBZ) is a leading professional services advisor to middle-market businesses nationwide. With ... Build developer-friendly tooling, paved-road patterns, and self-service guardrails that enable ...

... professional experience. 5+ years of experience in Data Science, Machine Learning, and AI software ... prompt engineering and LLM evaluation techniques Familiarity with frameworks such as LangChain ...

Senior Data Scientist

Cleveland, OH · On-site

$120 - $190/hr

... professional experience. * 5+ years of experience in Data Science, Machine Learning, and AI ... Strong understanding of prompt engineering and LLM evaluation techniques * Familiarity with ...

... professional experience. 5+ years of experience in Data Science, Machine Learning, and AI software ... prompt engineering and LLM evaluation techniques Familiarity with frameworks such as LangChain ...

Senior AI/ML Engineer

Dayton, OH · On-site

$99K - $225K/yr

Design, develop, and implement AI / ML models, including NLP, LLM-based pipelines, deep learning ... professional development, tuition assistance, work-life programs, and dependent care. Our ...

... professional experience. · 5+ years of experience in Data Science, Machine Learning, and AI ... engineering and LLM evaluation techniques · Familiarity with frameworks such as LangChain ...

... professional experience. • 5+ years of experience in Data Science, Machine Learning, and AI ... engineering and LLM evaluation techniques • Familiarity with frameworks such as LangChain ...

From LLM-powered copilots to custom integrations and automation, your work helps scale innovation ... Familiarity with DevOps practices, containerization (Docker, Kubernetes), and CI/CD pipelines for ...

AI/ML Engineer, Senior

Dayton, OH · On-site

$99 - $225/hr

You Have * 5+ years of experience developing ML models such as NLP, LLM, computer vision, deep ... leave, professional development, tuition assistance, work‑life programs, and dependent care.

Showing results 21-40

Professional Llm Developer information

What is a professional LLM developer?

Professional LLM Developers are software engineers or specialists who design, build, and optimize applications and systems that leverage large language models (LLMs) like GPT-4, Claude, or similar AI models. Their work often involves integrating LLMs into products, fine-tuning models for specific tasks, ensuring safe and ethical AI use, and improving performance. They may also create tools and frameworks that facilitate the deployment and scaling of LLM-powered applications. Their expertise combines software development, machine learning, and natural language processing.

What are the key skills and qualifications needed to thrive as a professional LLM developer?

To thrive as a Professional LLM Developer, you need expertise in machine learning, natural language processing, and strong programming skills in languages like Python, often supported by a degree in computer science or related fields. Familiarity with deep learning frameworks (such as PyTorch or TensorFlow), experience with large language model architectures, and knowledge of cloud platforms are typically required, along with certifications like TensorFlow Developer or AWS Certified Machine Learning. Strong problem-solving abilities, teamwork, and effective communication distinguish top performers in this role. These skills ensure the development, fine-tuning, and deployment of robust LLM solutions that meet business and technical needs.

What are some common challenges faced by professional LLM developers when deploying large language models in production environments?

Professional LLM Developers often encounter challenges such as optimizing model performance to balance accuracy with computational efficiency, managing latency for real-time applications, and ensuring data privacy and security. Additionally, integrating LLMs with existing systems and maintaining model versioning can be complex. Collaboration with cross-functional teams, such as data engineers and product managers, is essential to address these challenges and ensure the successful deployment and ongoing maintenance of LLM-driven solutions.

What is the difference between Professional Llm Developer vs Machine Learning Engineer?

AspectProfessional Llm DeveloperMachine Learning Engineer
CredentialsTypically requires advanced degrees in AI, NLP, or related fields; certifications in AI/MLOften holds degrees in computer science, data science, or engineering; certifications in ML frameworks
Work EnvironmentFocuses on developing and fine-tuning large language models, often in research or specialized AI teamsDesigns, builds, and deploys ML models across various applications, in industry or tech companies
Industry UsagePrimarily in AI research, NLP, and companies developing LLM-based productsUsed across tech, finance, healthcare, and other sectors for predictive modeling and automation

While both roles involve AI and machine learning, a Professional Llm Developer specializes in large language models and NLP, whereas a Machine Learning Engineer works on a broader range of ML applications and models across industries.

What are the most commonly searched types of Llm Developer jobs in Ohio?

The most popular types of Llm Developer jobs in Ohio are:

What are popular job titles related to Professional Llm Developer jobs in Ohio?

For Professional Llm Developer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Professional Llm Developer jobs in Ohio look for?

The top searched job categories for Professional Llm Developer jobs in Ohio are:

What cities in Ohio are hiring for Professional Llm Developer jobs?

Cities in Ohio with the most Professional Llm Developer job openings:

Senior Product Security Engineer

Myers and Stauffer

Independence, OH • Hybrid

Full-time

Posted 25 days ago


Job description

#LI-CR2 #LI-Hybrid

CBIZ, Inc. (NYSE: CBZ) is a leading professional services advisor to middle-market businesses nationwide. With industry knowledge and expertise in accounting, tax, advisory, benefits, insurance, and technology, CBIZ delivers actionable insights to help clients anticipate what is next and discover new ways to accelerate growth. CBIZ has more than 9,500 team members across 23 major markets coast to coast.

CBIZ strives to be our team members' employer of choice by creating an environment where team members are appreciated, recognized for their contributions, and provided with opportunities to grow, both personally and professionally, throughout their careers.

Together, CBIZ and CBIZ CPAs are ranked as one of the top providers of accounting services in the United States. CBIZ CPAs is an independent CPA firm that provides audit, review and attest services, while CBIZ provides business consulting, tax and financial services. In certain jurisdictions, CBIZ CPAs operates under its previous name, Mayer Hoffman McCann P.C.

Minimum Qualifications 

  • College Degree or equivalent required
  • 8 years related experience
  • Expert technical knowledge
  • Knowledge of industry regulations
  • Ability to lead and coordinate the team activities of others
  • Ability to formulate, document and recommend new policies and procedures
  • Able to work in and lead a team
  • Demonstrated ability to communicate verbally and in writing throughout all levels of an organization, both internally and externally
  • Ability to travel as required by business and on-call availability

The Senior Product Security Engineer is a deeply technical, hands-on engineering and architect-level role responsible for establishing and leading the Product Security function at CBIZ. As the first dedicated hire in this domain, this position serves as the single point of accountability for product security across the enterprise - defining strategy, building the program from the ground up, and operating as a trusted architect and advisor to development, engineering, platform, and AI teams.

Operating within a matrix organization, the role champions a security-first mindset across business groups, embeds secure-by-design principles into the Software Development Lifecycle (SDLC), and leads the transformation to a mature Secure SDLC with a DevSecOps focus. The engineer acts as a guiding authority on secure coding, threat modeling, application architecture, AI/LLM security, and software supply chain integrity.

This role requires an experienced builder with a strong coding background, demonstrated AI security expertise, and the ability to influence without direct authority - operating as a credible technical peer to senior developers and AI engineers alike.

Essential Functions and Primary Duties

Product Security Strategy & Architecture

  • Define and own the enterprise Product Security strategy, roadmap, reference architectures, and secure design patterns for web, mobile, API, microservices, serverless, and AI-enabled applications.

  • Serve as the Product Security Architect for major initiatives, providing authoritative guidance on authentication, authorization, session management, encryption, key management, secrets handling, and API security.

  • Establish secure-by-design standards, control libraries, and engineering guardrails that scale across product lines and business units.

Secure SDLC & DevSecOps Enablement

  • Lead the transition from traditional SDLC to a mature Secure SDLC with embedded DevSecOps controls, integrating security gates into every phase including design, code, build, test, deploy, and operate.

  • Architect and operationalize security automation including SAST, DAST, SCA, container image scanning, and secrets detection.

  • Define vulnerability remediation of SLAs and drive measurable reduction in mean-time-to-remediate.

  • Build developer-friendly tooling, paved-road patterns, and self-service guardrails that enable engineering velocity without compromising security.

AI Security & AI Engineering Partnership

  • Act as the dedicated security partner to CBIZ's AI engineering team, reviewing AI/ML configurations, agent designs, model integrations, and deployment patterns to ensure they meet enterprise security and privacy standards.

  • Establish AI security best practices and guardrails for generative AI, agentic workflows, RAG pipelines, and LLM-powered applications, aligned to the OWASP Top 10 for LLM Applications including prompt injection, insecure output handling, training data poisoning, supply chain vulnerabilities, sensitive information disclosure, excessive agency, and model theft.

  • Review and harden AI model configurations, system prompts, tool and function calling permissions, content filters, rate limits, and identity boundaries for agents operating against enterprise data.

  • Establish controls for AI-generated code review to ensure AI-assisted development does not bypass secure SDLC checkpoints.

  • Define data protection and access controls for AI workloads including grounding data governance, vector database security, and PII handling prompts and responses.

  • Partner with AI engineers on model risk management, red-teaming, and adversarial testing.

  • Stay current with the evolving AI regulatory landscape (NIST AI RMF, EU AI Act, ISO/IEC 42001) and translate requirements into engineering controls.

Threat Modeling & Secure Design Reviews

  • Facilitate threat modeling sessions using STRIDE, PASTA, and MITRE ATLAS for AI/ML systems producing actionable mitigations and ranked risk registers.

  • Conduct architecture and design reviews to identify weaknesses before code is written, partnering with solution architects and engineering leads.

Code Review & Vulnerability Management

  • Perform manual and tool-assisted secure code reviews against OWASP Top 10, CWE Top 25, and SANS 25, providing remediation guidance with corrected code where appropriate.

  • Triage scanner findings and own application vulnerability management workflows, SLA tracking, and executive reporting on AppSec posture.

Software Supply Chain Security

  • Define and enforce controls for third-party and open-source components, dependency hygiene, SBOM generation, and signed artifacts, including AI model provenance and dataset integrity.

  • Harden source repositories, build systems, and deployment environments against supply chain compromise.

Matrix Leadership & Security Mindset Advocacy

  • Navigate CBIZ's matrix organization to influence development, engineering, AI, platform, and product teams.

  • Act as the visible, accessible point of contact for application security, embedding into engineering rituals such as design reviews, architecture councils, and sprint planning.

  • Lead developer enablement programs including secure coding training, threat modeling workshops, a security champions network, and lunch-and-learn sessions across business groups.

Incident Response & Executive Reporting

  • Serve as the AppSec and AI security subject matter expert during incident response, escalations, and post-incident reviews.

  • Produce board-ready and executive-level reporting on AppSec maturity, AI security posture, key risk indicators, and program outcomes.

Preferred Qualifications

  • 8+ years of progressive experience in software engineering, application development, or platform engineering, with at least 4 years focused on product security, DevSecOps, or security architecture.

  • Mandatory hands-on coding background with proficiency in one or more modern languages such as Python, Java, C#/.NET, JavaScript/TypeScript, or Go, and the demonstrated ability to read, write, and review production code as a peer to senior developers.

  • Mandatory experience working directly with development, engineering, and AI/ML teams within a matrix environment.

  • Mandatory hands-on AI security experience, including reviewing AI/ML system architectures, securing LLM integrations, evaluating model configurations, and applying frameworks such as OWASP Top 10 for LLMs, MITRE ATLAS, and the NIST AI Risk Management Framework.

  • Deep expertise in Secure SDLC, OWASP Top 10, CWE Top 25, MITRE ATT&CK, and CVSS.

  • Hands-on experience with AppSec tooling such as SAST (Semgrep, CodeQL, SonarQube, Checkmarx, Veracode), DAST (Burp Suite, OWASP ZAP), SCA (Snyk, Black Duck), IaC scanning, and secrets detection.

  • Strong understanding of CI/CD platforms including GitHub Actions, GitLab CI, Azure DevOps, and Jenkins, with experience hardening pipeline security.

  • Cloud security expertise across Microsoft Azure and AWS, including IAM, container security (Kubernetes), workload protection, and CNAPP platforms.

  • Familiarity with API security (REST, GraphQL), authentication and authorization standards (OAuth 2.0, OIDC, SAML), and modern cryptography.

  • Demonstrated ability to influence without authority and navigate a matrix organization across multiple business groups.