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Vector Security Jobs in Ohio (NOW HIRING)

Deloitte

Google AI Lead Architect

Columbus, OH · On-site

$53.25 - $73.25/hr

... security, and cost. * Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment ...

TQL

AI Architect

Cincinnati, OH · On-site

$60.50 - $79.50/hr

Experience with embeddings, vector databases, RAG patterns, LangChain, Semantic Kernel and MLflow ... Strong understanding of data modeling, governance, lineage and security* Strong communication ...

Total Quality Logistics

AI Architect

Cincinnati, OH · On-site

Experience with embeddings, vector databases, RAG patterns, LangChain, Semantic Kernel and MLflow ... Strong understanding of data modeling, governance, lineage and security * Strong communication ...

Monitise

Director, AI - Cyber Security I

Columbus, OH · On-site

... vector search, and knowledge retrieval systems. * Lead the engineering and delivery of scalable, cloud-native AI security platforms on Google Cloud using tools such as Vertex AI, Gemini, BigQuery ...

Frontier Technology Inc.

AI/ML Engineer

Dayton, OH · Remote

... security missions. This role focuses on execution in oversight, ideal for an engineer who thrives ... Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval ...

J.P. Morgan

Senior Lead Data Architect

Columbus, OH · On-site

$65 - $87/hr

... vector search/RAG), agent toolchains (planning/execution), guardrails, access controls/risk ... Familiarity with data governance, security, and compliance standards Preferred qualifications ...

Resonant Sciences, LLC

RF Engineer

Dayton, OH · On-site

Experience using RF test equipment such as: vector network analyzers, spectrum analyzers ... CITIZENSHIP/SECURITY CLEARANCE: * U.S. Citizenship required. Must be eligible to obtain and/or ...

Deloitte

AI Engineer Consultant

Columbus, OH · Hybrid

Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ... security/compliance efforts; familiarity with enterprise security controls (IAM, encryption ...

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Showing results 41-60

All JobsVector Security JobsVector Security Jobs in Ohio

Vector Security information

See Ohio salary details

$12

$17

$22

How much do vector security jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for vector security in Ohio is $17.56, according to ZipRecruiter salary data. Most workers in this role earn between $16.01 and $18.27 per hour, depending on experience, location, and employer.

What does Vector Security do?

Vector Security is a company that provides security solutions, including alarm systems, video surveillance, access control, and monitoring services for residential and commercial clients. Employees in security-related roles may need knowledge of security systems, installation skills, and certifications such as NICET or similar. The company focuses on protecting property and ensuring safety through integrated security technology.

What is Vector Security?

Vector Security is a company that specializes in providing security solutions for both residential and business customers. Their services include alarm systems, video surveillance, access control, fire and carbon monoxide detection, and smart home automation. They also offer 24/7 professional monitoring to ensure rapid response in the event of an emergency. Vector Security operates across North America and customizes their solutions based on individual client needs.

What are some common challenges faced by Vector Security technicians in the field, and how can they prepare for them?

Vector Security technicians often encounter challenges such as troubleshooting complex alarm or surveillance systems in diverse environments and addressing customer concerns on-site. Weather conditions, tight schedules, and rapidly evolving technology can also add complexity to their daily tasks. Being adaptable, maintaining strong communication with both customers and the support team, and staying up-to-date with the latest product training can help technicians overcome these challenges and deliver excellent service.

What are the key skills and qualifications needed to thrive as a security systems technician at Vector Security, and why are they important?

To thrive as a Security Systems Technician at Vector Security, you need a solid understanding of electronic security systems, wiring, troubleshooting, and typically a high school diploma or equivalent, with some positions requiring industry certifications. Familiarity with alarm panels, CCTV systems, access control software, and certifications like NICET or manufacturer-specific training are highly valued. Attention to detail, strong problem-solving skills, and effective communication help technicians excel in both technical tasks and customer interactions. These skills are crucial for ensuring the reliable installation and maintenance of security systems, directly impacting client safety and satisfaction.

What is the difference between Vector Security vs Security Technician?

AspectVector SecuritySecurity Technician
Required CertificationsAlarm system certifications, security licensesSecurity system certifications, technical training
Work EnvironmentInstallation, monitoring, and maintenance of security systemsInstalling, repairing, and troubleshooting security equipment
Employer & Industry UsageSecurity companies, alarm service providersSecurity service providers, electronics retailers
Common Search & ComparisonYesYes

Vector Security primarily focuses on alarm system installation, monitoring, and security solutions, often involving customer service and system management. Security Technicians are more hands-on, specializing in installing and repairing security hardware. While both roles require technical certifications and work within the security industry, Vector Security roles may include monitoring responsibilities, whereas Security Technicians focus on technical installation and maintenance.

What are popular job titles related to Vector Security jobs in Ohio? For Vector Security jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Vector Security jobs in Ohio look for? The top searched job categories for Vector Security jobs in Ohio are:
What cities in Ohio are hiring for Vector Security jobs? Cities in Ohio with the most Vector Security job openings:
Vector Security jobs near you
Infographic showing various Vector Security job openings in Ohio as of August 2026, with employment types broken down into 85% Full Time, 10% Part Time, and 5% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $36,521 per year, or $17.6 per hour.

Google AI Lead Architect

Deloitte

Columbus, OH • On-site

$53.25 - $73.25/hr

Full-time

Re-posted 21 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services

Job description

Google AI Lead Architect/AI & Engineering:

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8-31-2026
Work you'll do:

  • Architect and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini; optimize for scalability, reliability, security, and cost.
  • Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring.
  • Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability.
  • Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build.
  • Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform; enforce application and agentic design patterns.
  • Implement security and governance for AI/ML systems (data privacy, model poisoning, adversarial attacks); apply Gemini safety features and enterprise guardrails.

Responsibilities include:

  • Architect and Design: Lead the design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production. This includes defining the technical architecture, selecting appropriate technologies, and ensuring solutions are robust, scalable, and secure.
  • LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis on production-level performance and reliability.
  • Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
  • Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform (AWS, Azure, GCP). Leverage a wide range of hyperscaler tools and services, including containers (Docker, Kubernetes), serverless functions, and managed databases. Should have experience in leveraging various GenAI tools to accelerate software development life cycle.
  • Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities such as data privacy concerns, model poisoning, and adversarial attacks.
  • Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and maintainable software systems.

 Required Qualifications

  • Bachelor's degree in Computer Science, Engineering or a related technical field.
  • 8+ years' experience as a Software or Solution Architect, with a strong focus on application development and scaling solutions for production environments.
  • 5+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
  • 4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
  • 3+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
  • 3+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
  • 3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
  • 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years' production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
  • Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
  • Experience implementing multiple AI solutions in a professional, real-world environment.
  • Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
  • Familiarity with various hyperscaler tools and services.
  • Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred Qualifications:

  • Google Professional Machine Learning Engineer certification or the equivalent ML certification.
  • Master's degree in technology-related discipline.
  •  2+ years's leading high performance, results driven engineering teams delivering AI platforms or applications.
  • 1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)

Wages + Salary

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Google AI Lead Architect/AI & Engineering:

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8-31-2026
Work you'll do:

  • Architect and deliver enterprise AI platforms and applications on Google Cloud using Vertex AI and Gemini; optimize for scalability, reliability, security, and cost.
  • Design, fine-tune, evaluate, and govern LLM solutions with Gemini on Vertex AI (prompt/tool/function calling, safety policies, Vector Search, evaluation); implement deployment, inference optimization, and monitoring.
  • Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability.
  • Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines and Cloud Build.
  • Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform; enforce application and agentic design patterns.
  • Implement security and governance for AI/ML systems (data privacy, model poisoning, adversarial attacks); apply Gemini safety features and enterprise guardrails.

Responsibilities include:

  • Architect and Design: Lead the design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production. This includes defining the technical architecture, selecting appropriate technologies, and ensuring solutions are robust, scalable, and secure.
  • LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an emphasis on production-level performance and reliability.
  • Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
  • Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform (AWS, Azure, GCP). Leverage a wide range of hyperscaler tools and services, including containers (Docker, Kubernetes), serverless functions, and managed databases. Should have experience in leveraging various GenAI tools to accelerate software development life cycle.
  • Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities such as data privacy concerns, model poisoning, and adversarial attacks.
  • Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient and maintainable software systems.

 Required Qualifications

  • Bachelor's degree in Computer Science, Engineering or a related technical field.
  • 8+ years' experience as a Software or Solution Architect, with a strong focus on application development and scaling solutions for production environments.
  • 5+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
  • 4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
  • 3+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
  • 3+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
  • 3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
  • 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years' production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
  • Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
  • Experience implementing multiple AI solutions in a professional, real-world environment.
  • Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
  • Familiarity with various hyperscaler tools and services.
  • Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred Qualifications:

  • Google Professional Machine Learning Engineer certification or the equivalent ML certification.
  • Master's degree in technology-related discipline.
  •  2+ years's leading high performance, results driven engineering teams delivering AI platforms or applications.
  • 1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)

Wages + Salary

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of...

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