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Prompt Engineer Jobs in Raleigh, NC (NOW HIRING)

Lead Forward Deployed Engineer, Palantir

Raleigh, NC · On-site

$99K - $131K/yr

Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls * Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid ...

Lead Forward Deployed Engineer, Snowflake

Raleigh, NC · On-site

$99K - $131K/yr

Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls * Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid ...

Senior Systems Engineer

Raleigh, NC · On-site +1

$101K - $139K/yr

... prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g., scikit-learn, MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level). Consulting ...

New

Deliver Generative AI solutions, including prompt engineering and retrieval/grounding patterns, and apply quantitative and qualitative evaluation before scaling to production. * Design AI assistants ...

Lead Forward Deployed Engineer - AWS

Raleigh, NC · On-site

$99K - $131K/yr

Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls * Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid ...

Software Engineer, Backend

Cary, NC · On-site

$152K - $219K/yr

Able to comment on the difference between 'prompt engineering', 'context engineering', and 'agentic engineering'. Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and ...

Software Engineer, Backend

Durham, NC · On-site

$152K - $219K/yr

Able to comment on the difference between 'prompt engineering', 'context engineering', and 'agentic engineering'. Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and ...

... prompt engineering for LLM optimization - Implementing data integration solutions using AWS, Azure, GCP - Utilizing AWS CloudFormation, Azure Resource Manager, Terraform - Building and deploying ...

Staff AI Engineer

Raleigh, NC · On-site +1

$210K - $290K/yr

You can speak to failure modes, cost optimization, prompt engineering patterns, and model selection trade-offs from experience. * Designed and operated AI-assisted code generation or review systems ...

Staff AI Engineer

Raleigh, NC · Remote

$210K - $290K/yr

You can speak to failure modes, cost optimization, prompt engineering patterns, and model selection trade-offs from experience. * Designed and operated AI-assisted code generation or review systems ...

Senior Value Engineer - Manufacturing

Raleigh, NC · On-site

$88K - $121K/yr

Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, prompt engineering, and common ML libraries (LangChain, pandas, PyTorch). * Familiarity with IT/OT ...

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Prompt Engineer information

See Raleigh, NC salary details

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$45

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How much do prompt engineer jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for prompt engineer in Raleigh, NC is $45.77, according to ZipRecruiter salary data. Most workers in this role earn between $34.81 and $59.13 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Prompt Engineer position, and why are they important?

To thrive as a Prompt Engineer, you need a strong grasp of natural language processing (NLP), machine learning concepts, and experience crafting effective prompts for large language models, usually supported by a technical degree or relevant experience. Familiarity with tools such as OpenAI's API, Hugging Face, or other AI platforms, as well as knowledge of programming languages like Python, is highly valuable. Creative thinking, analytical problem-solving, and cross-functional communication skills help differentiate top candidates in this field. These abilities are crucial for optimizing AI outcomes and ensuring collaboration with both technical and non-technical teams.

What does a typical day look like for a Prompt Engineer?

A typical day for a Prompt Engineer involves designing, testing, and refining prompts to enhance the performance of AI language models, often collaborating closely with data scientists, software engineers, and product managers. You might analyze the results of model outputs, integrate user or stakeholder feedback, and iterate on prompt strategies to solve diverse business challenges. Your role will usually include documentation, troubleshooting, and keeping up with the latest advances in AI technologies. Expect a mix of independent work and regular team meetings in a dynamic, fast-evolving environment focused on innovation and improvement.

What engineer makes $500,000 a year?

Senior software engineers, especially those working in high-demand fields like AI, machine learning, or at major tech companies, can earn $500,000 or more annually through base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, specialized skills, and often leadership roles or equity compensation.

What is a Prompt Engineer job?

A Prompt Engineer is a professional who designs, refines, and optimizes prompts to improve interactions with AI models, such as ChatGPT. Their role involves understanding model behavior, crafting precise queries, and experimenting with phrasing to achieve desired outputs. They may work in AI research, software development, or content generation to maximize AI efficiency. Strong skills in language, logic, and sometimes coding are essential for success in this role.

Is prompt engineer still a thing?

Prompt engineering is an emerging role focused on designing effective prompts for AI language models. It is increasingly in demand as organizations seek to optimize AI interactions, often requiring skills in natural language processing and familiarity with tools like GPT. The role continues to grow alongside advancements in AI technology.

What exactly is prompt engineer work?

A prompt engineer designs and optimizes prompts used to interact with AI language models, ensuring accurate and relevant outputs. The role requires understanding of AI systems, natural language processing, and often involves testing and refining prompts to improve model performance. Skills in programming, data analysis, and familiarity with AI tools are commonly needed.

Is prompt engineer salary?

Prompt engineers typically earn salaries comparable to other AI and machine learning specialists, with average annual pay ranging from $80,000 to $150,000 depending on experience, location, and industry. Skills in natural language processing, prompt design, and familiarity with AI tools like GPT are highly valued and can influence compensation.
What are the most commonly searched types of Prompt Engineer jobs in Raleigh, NC? The most popular types of Prompt Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Prompt Engineer jobs? Cities near Raleigh, NC with the most Prompt Engineer job openings:
Infographic showing various Prompt Engineer job openings in Raleigh, NC as of July 2026, with employment types broken down into 80% Full Time, 8% Part Time, and 12% Contract. Highlights an 88% In-person, 4% Hybrid, and 8% Remote job distribution, with an average salary of $95,205 per year, or $45.8 per hour.
Lead Forward Deployed Engineer, Palantir

Lead Forward Deployed Engineer, Palantir

Deloitte

Raleigh, NC • On-site

$99K - $131K/yr

Other

Re-posted 19 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

60th of 148 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Lead Palantir FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

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.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Palantir including hands-on experience with one of the following key platforms; Foundry, AIP, Maven 
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $189,200 to $372,900.

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:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Lead Palantir FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients. You'll set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team. You'll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.

Client Engagement

  • Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk) and a phased plan from prototype to production and scaling
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements-contributing to pipeline development and deal shaping.

Cross-Functional Pod Leadership & Program Governance

  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health
  • Enforce delivery standards across the pod: sprint cadences, stakeholder communication plans, risk management, and quality gates
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs

GenAI Solution Development

  • Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below)
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls
  • Govern end-to-end RAG pipeline design-including ingestion, chunking, embedding, vector retrieval, and hybrid search-ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.

Engineering & Data Foundations

  • Review and contribute to production-quality code
  • Guide architecture of data pipelines powering GenAI use cases
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud)


The team

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.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Palantir including hands-on experience with one of the following key platforms; Foundry, AIP, Maven 
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $189,200 to $372,900.

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.

Education:Bachelor's DegreeEmployment Type:

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