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About This Role
Job ID
328834
Job Title: AI Prompt Engineer
Job Category: Engineering
Time Type: Full time
Minimum Clearance Required to Start: None
Employee Type: Regular
Percentage of Travel Required: Up to 10%
Type of Travel: Local
\* \* \* The Opportunity:
CACI is currently looking for a AI Prompt Engineer to join our BEAGLE (Border Enforcement Applications for Government Leading\-Edge Information Technology) Agile Solution Factory (ASF) Team supporting Customs and Border Control (CBP) client located in Northern Virginia! Join this passionate team of industry\-leading individuals supporting the best practices in Agile Software Development for the Department of Homeland Security (DHS).
As a member of the BEAGLE ASF Team, you will support the men and women charged with safeguarding the American people and enhancing the Nation’s safety, security, and prosperity. CBP agents and officers are on the front lines, every day, protecting our national security by combining customs, immigration, border security, and agricultural protection into one coordinated and supportive activity.
ASF programs thrive in a culture of innovation and are constantly seeking individuals who can bring creative ideas to solve complex problems, both technical and procedural at the team and portfolio levels.
More about this role:
We are seeking a highly creative, technically proficient, and detail\-oriented Prompt Engineer to join our growing AI team. This pivotal role will be responsible for designing, testing, and optimizing prompts for Large Language Models (LLMs) to achieve high\-quality, and reliable outputs for various use cases. You will be instrumental in translating complex requirements into effective AI interactions.
This role is ideal for someone who thrives on experimentation, understands how LLMs interpret language, and is passionate about unlocking the full potential of generative AI.
You will excel at developing innovative software solutions as part of a technically diverse and geographically disbursed team. A strong passion for AI technologies and experience with agile delivery and deploying software in short sprints.
Responsibilities:
- Prompt Design \& Optimization: Develop, refine, and iterate on prompts for various generative AI models (LLMs) to elicit desired behaviors, responses, and creative outputs.
- Iterative Testing \& Analysis: Conduct testing to compare prompt variations, analyze results drive continuous improvement.
- Collaboration: Work closely with multiple groups to integrate prompts to streamline manual processes.
- Research \& Development: Stay abreast of the latest advancements in LLMs, generative AI, and prompt engineering techniques.
- Fine\-tuning \& RAG Support: Provide input and collaborate on strategies for model fine\-tuning and Retrieval Augmented Generation (RAG) to further improve accuracy.
- Problem Solving: Debug unexpected model behaviors, identifying root causes within prompt structure, model limitations, or data context.
Qualifications:
*Required*
- Must be a U.S. Citizen with the ability to pass CBP background investigation, criteria include, but not limited to:
+ 3\-year check for felony convictions
+ 1 year check for illegal drug use
+ 1 year check for misconduct such as theft or fraud
- Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related field (equivalent experience may be considered in lieu of degree).
- Must be available to work a hybrid schedule with onsite requirements in Ashburn, VA
- 0–3 years of professional software development experience, internships, or relevant academic project work.
- 1\+ year of hands\-on experience working with Large Language Models (e.g., OpenAI GPT series, Llama, Gemini) or other generative AI models.
- Experience with at least one programming language (Python, JavaScript/TypeScript)
- Familiarity with prompt engineering techniques (few\-shot, chain\-of\-thought, structured outputs, function calling)
*Desired:*
- Problem\-solving skills, with a data\-driven approach to experimentation and optimization.
- Witten and verbal communication skills, with an ability to articulate complex technical concepts clearly.
- Ability to work independently and collaboratively in a fast\-paced, evolving environment.
- Exposure to RAG concepts, including embeddings and vector databases
- Understanding of AI safety considerations (e.g., prompt injection, bias, data privacy)
- Exposure to Agile/Scrum development environments
*
What You Can Expect:
A culture of integrity.
At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high\-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.
An environment of trust.
CACI values the unique contributions that every employee brings to our company and our customers \- every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.
A focus on continuous growth.
Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.
Pay Range:
There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
The proposed salary range for this position is:
$66,700 \- $133,300*CACI is* *an Equal Opportunity Employer.* *All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any* *other protected characteristic.*
Salary Context
This $66K-$133K range is in the lower quartile for Prompt Engineer roles in our dataset (median: $127K across 5 roles with salary data).
View full Prompt Engineer salary data →Role Details
About This Role
Prompt Engineers design, test, and optimize interactions with large language models. They build evaluation frameworks, craft system prompts, and develop techniques like chain-of-thought and few-shot learning to get consistent, reliable outputs. The role emerged alongside the GPT-3 era and has matured into a legitimate engineering discipline, not the 'just talk to the AI' job that early skeptics dismissed.
The work is more systematic than creative. You're running hundreds of prompt variations through evaluation suites, measuring output quality across edge cases, and building guardrails for production systems. When a prompt works 95% of the time but fails catastrophically on the other 5%, you need to find those failure modes and fix them before they hit users.
Across the 3,708 AI roles we're tracking, Prompt Engineer positions make up 0% of the market. At CACI International, this role fits into their broader AI and engineering organization.
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
What the Work Looks Like
A typical week involves designing evaluation datasets for new use cases, benchmarking prompt strategies against each other with statistical rigor, working with product teams to define 'good enough' output quality, and building the tooling that lets non-technical teammates iterate on prompts safely. You'll spend more time in spreadsheets and evaluation dashboards than you'd expect.
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
Skills Required
The core requirement is deep LLM experience: prompt design, RAG architectures, and evaluation methodology. Python is table stakes. Many roles also want experience with specific providers like OpenAI, Anthropic, or open-source models. Understanding tokenization, context windows, and the practical differences between model families (reasoning ability, instruction following, output format compliance) separates strong candidates from the crowd.
Evaluation skills are becoming the differentiator. Can you design a rubric that measures output quality? Can you build automated evaluation pipelines? Do you understand when to use human evaluation vs. LLM-as-judge vs. deterministic checks? Companies are moving past 'vibes-based' prompt testing and want engineers who bring measurement discipline.
Strong postings specify the LLM use cases (summarization, extraction, classification, generation), the evaluation methodology they expect, and the production environment. Weak postings just say 'prompt engineering experience' without context. Look for companies that mention evaluation frameworks and production deployment.
Compensation Benchmarks
Prompt Engineer roles pay a median of $140,000 based on 11 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($100K) sits 29% below the category median. Disclosed range: $66K to $133K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
CACI International AI Hiring
CACI International has 6 open AI roles right now. They're hiring across Data Scientist, Research Engineer, AI/ML Engineer, Prompt Engineer. Positions span Camp Smith, HI, US, Florham Park, NJ, US, Remote, US. Compensation range: $133K - $290K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Prompt Engineer roles include Technical Writer, NLP Researcher, Software Engineer.
From here, career progression typically leads toward AI Product Manager, LLM Engineer, AI Solutions Architect.
The best prompt engineers come from technical backgrounds and add LLM expertise, not the other way around. If you're coming from a non-technical role, invest heavily in Python, evaluation methodology, and understanding how LLMs work under the hood (tokenization, attention, context windows). The role will increasingly merge with LLM Engineering as the tools mature.
What to Expect in Interviews
Interviews focus on evaluation methodology and systematic thinking. You'll likely be asked to design a prompt for a specific use case, explain how you'd measure output quality, and walk through how you'd debug a prompt that works 90% of the time but fails on edge cases. Expect to discuss tokenization, context window management, and the tradeoffs between different prompting strategies (few-shot vs. chain-of-thought vs. tool use).
When evaluating opportunities: Strong postings specify the LLM use cases (summarization, extraction, classification, generation), the evaluation methodology they expect, and the production environment. Weak postings just say 'prompt engineering experience' without context. Look for companies that mention evaluation frameworks and production deployment.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Prompt engineering roles are still growing but the market is maturing. Early roles were broad and experimental. Now, companies know what they want: someone who can systematically improve LLM output quality, reduce costs by optimizing token usage, and build evaluation infrastructure. The roles that survive will be the ones that look more like engineering than copywriting.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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