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Manager Prompt Engineering Jobs in Delaware (NOW HIRING)

Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning • Frameworks: TensorFlow ... Strong communication, stakeholder management, and analytical thinking Company : ClifyX provides ...

The role involves collaborating with product managers, data scientists, and engineering teams to ... with Prompt Engineering and Model Fine-tuning • Experience with RAG (Retrieval Augmented ...

Responsibilities : • Work closely with product managers, data scientists, ML engineers, and other ... prompt engineering. Preferred : • Familiarity with the financial services industries. • ...

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Manager Prompt Engineering information

What is a Manager of Prompt Engineering?

A Manager of Prompt Engineering is a professional who leads teams focused on designing, developing, and optimizing prompts for artificial intelligence models, particularly large language models (LLMs) like ChatGPT. They oversee the creation of effective prompts to ensure AI systems provide accurate, relevant, and safe responses. This role involves collaborating with data scientists, engineers, and product managers, as well as setting best practices for prompt creation and evaluation. Additionally, they may be responsible for training team members and implementing strategies to improve prompt performance over time.

What are the key skills and qualifications needed to thrive as a Manager of Prompt Engineering, and why are they important?

To thrive as a Manager of Prompt Engineering, you need expertise in natural language processing, AI model deployment, and prompt design, typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), prompt engineering platforms, and version control systems is expected, along with experience managing technical teams. Strong leadership, problem-solving, and communication skills distinguish top performers in this role. These abilities are crucial for ensuring effective AI solutions, driving team productivity, and aligning prompt engineering initiatives with organizational goals.

How does a Manager of Prompt Engineering typically collaborate with cross-functional teams to optimize AI outputs?

As a Manager of Prompt Engineering, you will frequently collaborate with data scientists, software engineers, product managers, and UX designers to refine and optimize prompt strategies for AI models. This involves translating business requirements into effective prompt templates, conducting prompt experiments, and communicating findings to stakeholders. Regular cross-functional meetings and feedback sessions are common, ensuring that the AI outputs align with both technical capabilities and user needs. Building strong relationships across teams is essential for successfully iterating on prompt designs and deploying scalable solutions.
What are the most commonly searched types of Prompt Engineering jobs in Delaware? The most popular types of Prompt Engineering jobs in Delaware are:
What are popular job titles related to Manager Prompt Engineering jobs in Delaware? For Manager Prompt Engineering jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Manager Prompt Engineering jobs in Delaware look for? The top searched job categories for Manager Prompt Engineering jobs in Delaware are:
What cities in Delaware are hiring for Manager Prompt Engineering jobs? Cities in Delaware with the most Manager Prompt Engineering job openings:

$100K - $110K/yr

Full-time

Posted 7 days ago


Job description

GenAI Engineer
Design and develop AI/ML and Generative AI solutions for banking use cases including fraud detection, risk modeling, and customer analytics.
• Build, fine-tune, and deploy ML models and LLMs for credit scoring, AML, and automation
• Implement RAG-based GenAI applications using internal banking data
• Develop scalable data pipelines for training, validation, and real-time inference
• Collaborate with risk, compliance, finance, and business teams for AI solutions
• Ensure regulatory compliance and AI governance standards
• Implement data security, privacy, and access control mechanisms
• Integrate AI models into production using APIs and microservices
• Apply prompt engineering and model optimization techniques
• Monitor model performance, drift detection, and continuous improvement
• Develop explainable AI (XAI) for transparent decision-making
• Optimize cost, latency, and scalability of AI systems
• Troubleshoot AI/ML system issues across data and deployment layers
• Write efficient Python code using AI frameworks
• Follow MLOps best practices (CI/CD, automated deployment)
• Ensure responsible AI practices (bias, fairness, ethics)
• Mentor teams and contribute to enterprise AI platforms.
• Languages: Python
• AI/ML & GenAI: Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning
• Frameworks: TensorFlow, PyTorch
• GenAI Tools: LangChain, LlamaIndex
• Vector DB: Pinecone, FAISS
• Cloud Technologies: AWS / Azure / GCP
• Data Pipelines: ETL/ELT, Real-time & Batch Processing
• Integration: APIs, Microservices
• Concepts: RAG Architecture, XAI, Model Optimization
• Methodologies: Agile/Scrum, MLOps (CI/CD, Model Versioning, Deployment)
• Compliance: Banking regulations (SR 11-7, GDPR), Model Risk Management
• Soft Skills: Strong communication, stakeholder management, and analytical thinking
Salary Range- $100,000-$110,000 a year
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