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Director Prompt Engineer Jobs in Ohio (NOW HIRING)

Flexjet is seeking a Director of AI Engineering to lead the design, deployment, and ... RAG), prompt orchestration, model governance and guardrails, and cost optimization strategies.

POSITION SUMMARY Flexjet is seeking a Director of AI Engineering to lead the design, deployment ... prompt orchestration, model governance and guardrails, and cost optimization strategies. • Strong ...

Flexjet is seeking a Director of AI Engineering to lead the design, deployment, and ... RAG), prompt orchestration, model governance and guardrails, and cost optimization strategies.

Data Scientist

Dublin, OH · On-site

$120 - $160/hr

Direct experience with Prompt Engineering, Agent Engines, Agent Evaluation, and Agent Observation frameworks.* Experience with GCP Cloud Platform, including GCP Cloud Functions and BigQuery.

New

AI/ML Software Engineer

Evendale, OH · On-site

$95K - $140K/yr

... a direct impact on the future of flight. Key Responsibilities: * Design, build, and maintain ... Solid understanding of AI/ML concepts, including LLMs and prompt engineering * Experience with ...

Showing results 21-40

Director Prompt Engineer information

What is a director prompt engineer?

Director Prompt Engineers are professionals who oversee and lead teams in designing, developing, and refining prompts for artificial intelligence (AI) models, such as large language models. They are responsible for setting prompt engineering strategies, ensuring prompt quality, and collaborating with cross-functional teams to align AI outputs with business goals. Their role often includes managing prompt engineers, establishing best practices, and driving innovation in how AI systems interpret and respond to human input. Director Prompt Engineers play a critical role in shaping the effectiveness and accuracy of AI applications across various industries.

Are director prompt engineers still in demand?

Director prompt engineers are increasingly in demand as organizations seek expertise in designing and optimizing AI prompts for large language models. The role requires strong skills in AI, natural language processing, and strategic thinking, with demand driven by the growth of AI applications across industries.

What is the difference between Director Prompt Engineer vs Prompt Engineer?

AspectDirector Prompt EngineerPrompt Engineer
ResponsibilitiesOversees AI prompt strategies, manages teams, and aligns AI outputs with business goalsDesigns and develops prompts to optimize AI model responses
Required SkillsAdvanced AI knowledge, leadership, project managementStrong prompt design, AI understanding, technical writing
Work EnvironmentStrategic, managerial, cross-functional teamsTechnical, focused on prompt creation and testing
Industry UsageUsed in organizations integrating AI at a strategic levelCommon in AI development, research, and product teams

The main difference is that a Director Prompt Engineer leads AI prompt initiatives and manages teams, while a Prompt Engineer focuses on designing effective prompts. The director role involves strategic oversight, whereas the prompt engineer role is more technical and hands-on.

What skills and qualifications are needed to thrive as a director prompt engineer?

To thrive as a Director Prompt Engineer, you need deep expertise in natural language processing, AI model development, and prompt engineering, supported by an advanced degree in computer science or a related field. Proficiency with machine learning frameworks, prompt optimization tools, and familiarity with platforms like OpenAI API is essential, along with experience in managing technical teams. Exceptional communication, strategic thinking, and leadership skills help drive innovation and effectively guide cross-functional teams. These skills ensure the delivery of high-performing AI solutions and foster a collaborative environment for continuous improvement in prompt engineering.

How does a director prompt engineer collaborate with cross-functional teams to implement AI-driven solutions?

A Director Prompt Engineer regularly works with data scientists, product managers, software engineers, and UX designers to ensure that AI prompts align with business objectives and user needs. This collaboration often involves leading brainstorming sessions, reviewing prompt performance analytics, and iterating based on feedback from both technical and non-technical stakeholders. By maintaining clear communication and a shared vision across teams, the Director ensures that prompt engineering strategies are seamlessly integrated into product development cycles. This role also mentors team members and establishes best practices, fostering a culture of continuous learning and innovation.
What are the most commonly searched types of Prompt Engineer jobs in Ohio? The most popular types of Prompt Engineer jobs in Ohio are:
What are popular job titles related to Director Prompt Engineer jobs in Ohio? For Director Prompt Engineer jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Director Prompt Engineer jobs? Cities in Ohio with the most Director Prompt Engineer job openings:

Director of AI Engineering

Flexjet

Cleveland, OH • On-site

$180 - $300/hr

Other

This job post has expired today. Applications are no longer accepted.


Flexjet rating

8.2

Company rating: 8.2 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

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Job description

Current job opportunities are posted here as they become available.

Flexjet is seeking a Director of AI Engineering to lead the design, deployment, and operationalization of enterprise‑scale machine learning and generative AI systems. This role is responsible for building and managing the infrastructure, systems, and processes required to reliably deploy and maintain AI solutions in production. Combine strong engineering leadership with deep expertise in MLOps, cloud infrastructure, model lifecycle management, and Generative AI deployment. Lead a team of AI engineers and MLOps specialists to ensure scalable, secure, and compliant AI systems across the organization.

DUTIES & RESPONSIBILITIES
  • Lead the strategy, architecture, and implementation of enterprise AI, Generative AI, and MLOps platforms while establishing standards for model development, deployment, monitoring, governance, and lifecycle management.
  • Design and scale cloud‑native AI infrastructure, including distributed compute environments, containerized platforms, CI/CD pipelines, and cost‑optimized ML operations.
  • Oversee the production deployment of machine learning and LLM‑powered applications, including RAG solutions, AI copilots, model evaluation frameworks, guardrails, and automated retraining processes.
  • Ensure compliance with responsible AI, security, risk management, data privacy, auditability, reproducibility, documentation, and regulatory requirements.
  • Build and manage reusable AI platform services and frameworks that support multiple data science and engineering teams.
  • Lead, mentor, and grow teams of AI Engineers and MLOps Engineers, fostering engineering excellence, innovation, talent development, and performance accountability.
  • Partner with Data Scientists, Software Engineering, Security, DevOps, and Product leadership teams to drive enterprise AI adoption and align technical strategy with business objectives.
  • Communicate AI platform vision, roadmap, and operational performance to executive stakeholders.
EDUCATION & EXPERIENCE
  • Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or an equivalent combination of education, training, and relevant professional experience.
  • 10+ years of experience in software engineering, machine learning engineering, platform engineering, MLOps, or DevOps.
  • 5+ years of leadership experience managing and mentoring technical teams in fast‑paced, technology‑driven environments.
  • Experience implementing and deploying complex and integrated information systems.
  • Proven experience in leading application development teams in an enterprise environment.
  • Experience working with Agile methodology.
  • Experience in managing large projects including setting deadlines, identifying interdependencies, communicating with stakeholders, gathering requirements, and setting expectations.
REQUIRED TECHNICAL SKILLS & QUALIFICATIONS
  • Strong experience with MLOps and platform engineering, including model lifecycle management, CI/CD, model versioning, feature stores, experiment tracking, and automated retraining pipelines.
  • Proficiency with cloud and infrastructure technologies, including AWS, Azure, or Google Cloud Platform (GCP), Kubernetes, Docker, Terraform, and distributed systems.
  • Expertise in machine learning systems, including model deployment, monitoring and observability, data pipelines, and real‑time inference architectures.
  • Experience with Generative AI and LLM technologies, including LLM deployment, Retrieval‑Augmented Generation (RAG), prompt orchestration, model governance and guardrails, and cost optimization strategies.
  • Strong programming skills in Python, SQL, Bash, Git, and CI/CD tools.
PREFFERED QUALIFICATIONS
  • Experience deploying Generative AI and LLM solutions in large‑scale enterprise environments.
  • Experience designing and supporting multi‑tenant AI/ML platforms.
  • Familiarity with RAG architectures, vector databases, and LLM evaluation frameworks.
  • Experience managing GPU infrastructure and distributed training workloads.
  • Knowledge of AI security, governance, risk management, and regulatory compliance frameworks.
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