ChatGPT as an Adversarial Tool for Job Applications

Do you hear that, Mr. Anderson? That is the sound of inevitability.

The job market is getting tougher, and employers are using artificial intelligence (AI) to speed up hiring. AI algorithms help them quickly check resumes by looking at education, work experience, and skills to see if they match the job requirements. These tools make the initial screening process faster by highlighting candidates who fit the job criteria well. However, AI is just one part of the hiring process. Job seekers need to understand how these systems work to better navigate today's job market.

What if I told you that everything you know is a lie?

AI tools look at resumes by comparing the applicant’s qualifications—like education, work experience, and skills—with what is needed for the job. This creates a score to show how well a resume matches the job’s requirements.

This employer may use an artificial intelligence algorithm to provide an initial comparison of an applicant’s education, experience, and skills against the education, experience and skill requirements in the job description.

This analysis produces a Profile Relevancy score, which is intended to be one of many factors that a potential employer will review in making its interview decisions; there are no cut off scores and all applications are visible to employers.

The Profile Relevancy score for applicants who opt out will be listed as “Not Available.”

Even though human recruiters ultimately review resumes, the AI score often plays a crucial role in determining which resumes get the most attention. While all resumes are visible, not all receive equal scrutiny. A resume marked as “Not Available” due to opting out of AI evaluation doesn’t get the same level of consideration as those that pass the algorithm's filters.

Upon further research, I found the terms and conditions for that tool, provided by ADP.

4. Is Candidate Relevancy an automated employment decision tool covered by New York City Local Law 144 (“the NYC Ordinance”)?

The NYC Ordinance covers automated screening or selection tools that provide “output”—such as scores, classifications, or recommendations—to an employer, and which are used to significantly assist or substitute a human’s decision-making process. Under the NYC Ordinance, to substantially assist or substitute a human’s decision-making process means:

(1) to rely solely on a simplified output without consideration to other factors; (2) to use a simplified output as a consideration in a list of criteria but weight the output more heavily than other criteria the set; or (3) to use the output to overrule human decision-making conclusions.

Candidate Relevancy is not intended by ADP to be relied upon solely by employers in making employment decisions and is not meant to substantially assist or replace discretionary decision making in employment decisions. Moreover, Candidate Relevancy is not intended to be used as a criterion that is weighted more than any other criterion in making employment decisions and is not intended to be used to overrule conclusions derived from other factors, including human decision-making.

Candidate Relevancy is intended to be one source of assistance in helping to prioritize candidates selected for next steps. Education, skills, and experience must be evaluated and validated by employers through person-to-person interviews and background checks, among other things. Candidate Relevancy is not intended to replace human judgment during any step of the recruitment process and is designed in such a way that there are no cut-off scores that would eliminate candidates from being visible to employers in the user interface. Employers are thereby provided access to all candidates, enabling them to make human decisions on which candidates to pursue.

If Candidate Relevancy is used as intended by ADP, ADP does not believe Candidate Relevancy to be an automated employment decision tool as defined by the New York City Ordinance and its related final rules.

Nothing herein is intended to be a legal opinion and does not constitute legal advice. You should consult with an attorney before taking any action in reliance on the information provided herein including whether Candidate Relevancy is an automated employment decision tool.

ADP isn't even willing to stand behind this tool. You need your own lawyer to decide wether your use is compliant.

To make a strong impression early in the process, it’s essential to optimize your resume for AI tools. Understanding how to align your resume with AI criteria can significantly enhance its visibility and increase your chances of standing out in the initial screening.

I can only show you the door. You’re the one that has to walk through it.

With AI handling more of the initial screening, traditional methods of tailoring resumes may not be as effective. In the past, candidates put a lot of effort into customizing their resumes for each job, hoping to match their qualifications with the job’s needs. Now, the focus has shifted to making resumes that perform well in AI scans.

AI systems check resumes by looking at keywords and qualifications. They process each resume individually and may have biases based on their training data. This means that if a resume doesn’t fit perfectly with what the AI is looking for, it might be overlooked, even if the candidate is qualified.

It’s not a problem if you know what you’re doing.

In today’s job market, using AI tools to improve your resume is crucial. I use large language models (LLMs) to enhance my resume and have seen significant benefits. These tools can review your resume, spot weaknesses, and suggest changes to better match the job requirements.

Here is information about my company: Here, I paste in their homepage, their about page, and their careers page.

I am hiring for this position: Here, I paste in the job description.

Why should we decline to hire this resume?

As a hiring manager, my goal is to sift through hundreds of resumes to find the top candidates for an interview. I focus on whether a candidate can do the job. However, I recognize that this approach might be rare.

In many hiring processes, the focus often shifts to finding reasons to discard resumes rather than identifying the best candidates. I’ve experienced firsthand how bias and preconceived notions can cloud judgment—like when a director made discriminatory assumptions based on a candidate’s name and graduation year. Despite raising concerns, nothing changed.

I tend to apply for roles where I genuinely believe I’m a strong fit, knowing my skills and experience well. But this self-awareness can create a bias. The reviewer only sees what’s on the page.

That’s where the large language models (LLMs) come in. Their feedback can be a reality check, helping to refine and elevate a resume by pointing out areas for improvement that might not be evident otherwise. This process ensures that the final resume is not only polished but also optimally tailored to meet the expectations of an AI-driven hiring system.

Case Study 1: Engineering Manager Role

I applied for an Engineering Manager position at a company specializing in cloud-based software solutions for home healthcare. This company focuses on managing care delivery, scheduling, and billing.

To improve my chances, I used a large language model (LLM) to review my resume. The LLM identified areas where my resume did not fully align with the job requirements, such as my limited experience in the healthcare industry. After addressing these issues and updating my resume, the LLM recognized my strong technical skills and leadership experience, suggesting that I was still a strong candidate for the role despite the initial concerns.

When evaluating a resume like Evan d’Entremont's for the Engineering Manager position at company, there are several reasons you might consider declining to hire him based on potential misalignments with the job requirements and company culture:

1. Lack of Direct Healthcare Industry Experience: company operates in the home healthcare software industry, which has unique challenges and regulatory requirements. Evan’s experience spans various sectors (e.g., sports, industrial controls, and web development) but does not directly involve healthcare, clinical care, or medical software. This gap could be significant if deep healthcare domain expertise or understanding of healthcare-related compliance is critical.
2. Limited Formal Education in Engineering/Computer Science: Although Evan has substantial experience, his formal education in engineering and computer science appears incomplete. While experience can sometimes outweigh formal education, company might prioritize candidates with a completed degree, especially if technical leadership in a specialized domain like healthcare software is a concern.
3. Potential Misalignment in Technology Stack: company may prioritize candidates with experience in specific technologies relevant to their stack or future roadmap. While Evan has extensive experience in PHP, Python, and other technologies, there is no mention of experience with cloud-native development, microservices, or other modern SaaS-related technologies that could be key at company.
4. Leadership Experience in Specialized Teams: company’s role involves leading a team within the Care Planning and Delivery space, which demands understanding both technical and clinical complexities. Evan’s leadership experience, though substantial, has been in general software development rather than in a specialized or regulated environment like healthcare, which could be a critical distinction for the role.
5. Cultural and Industry Fit: company emphasizes an inclusive and transparent culture with a specific focus on home healthcare innovation. Evan’s resume does not highlight any experience in fostering innovation in such a specialized environment or any experience in an organization with a strong emphasis on diversity and inclusion. This might be a consideration depending on how crucial cultural alignment is to company.

While Evan's resume shows strong technical and leadership capabilities, these potential gaps could be why he might not be the best fit for the Engineering Manager role at company.

Damn.

I addressed the concerns with the LLM, which persistently highlighted my shortcomings. When I reached the limit of my defense, I asked, "Should we hire this person?"

Based on Evan d’Entremont’s resume and the requirements for the Engineering Manager role at company, here are some key considerations to help decide whether to hire him:

Strengths

1. Relevant Experience: Managed global teams effectively at Aylo and Guest Networks, which matches company's need for experience with distributed, asynchronous teams. Demonstrated expertise in software development, incident management, and compliance—important for company’s focus on delivering home healthcare software.
2. Technical Skills: Hands-on experience with PHP, Python, and databases aligns with the technical environment at company. Proven ability to architect solutions and improve system performance and reliability, relevant to the responsibilities of maintaining and developing features in company’s application.
3. Leadership and Team Management: Successfully led and mentored teams, optimizing workflows and promoting internal leadership. This experience fits well with company’s emphasis on team development and performance management.
4. Agile and Continuous Delivery: Applied Agile methodologies and led continuous delivery initiatives, aligning with company’s use of Scrum/Agile practices.
5. Compliance and Safety: Experience with compliance-focused projects and working under strict regulations is relevant to company’s focus on regulatory adherence in healthcare.

Potential Concerns

1. Company Fit: While Evan has strong technical and leadership skills, it's important to assess whether his management style and approach align with company’s company culture and values, particularly regarding transparency, collaboration, and inclusion.

Recommendation

Consider Hiring: Evan’s extensive experience managing global teams, technical expertise, and familiarity with agile methodologies make him a strong candidate for the Engineering Manager role at company. His background aligns well with the job requirements, and his ability to balance hands-on development with strategic oversight is a valuable asset.

Next Steps:

1. Interview: Conduct a thorough interview to discuss his recent layoff, his approach to team management, and his fit with company’s culture and values.
2. Reference Check: Obtain references from previous employers to verify his achievements and work style.

If Evan’s interview and references confirm his suitability, he would likely be a good fit for the position.

I may not have been the perfect match on paper, but I’m confident I could excel in the role. Without the challenge of reviewing my resume through an LLM, I might have submitted a less effective version.

Case Study 2: High-Tech Cloud API Management

For a position with a leading provider of cloud-native API management solutions, known for its high-performance and scalable technology, I again used an LLM to assess my resume.

Here are reasons why Evan d’Entremont might not be the ideal fit for the role:

1. Lack of Specific Kubernetes Experience

1. Kubernetes-Native Architecture: company emphasizes its Kubernetes-native architecture. If Evan’s Kubernetes experience at Guest Networks did not specifically involve leveraging Kubernetes-native features or if his work focused more on general multi-region setups rather than Kubernetes-specific optimizations, it might be a gap.
2. Experience with Specific API Protocols: company supports a wide array of modern protocols like REST, GraphQL, gRPC, and Kafka. While Evan has experience with REST APIs and protobuf, if his experience with these specific protocols is limited or lacks depth compared to company’s needs, it could be a concern.
3. Open Source Contribution: company prides itself on its open-source roots and community involvement. If Evan’s background is more focused on proprietary technologies and he has limited experience with open-source contributions or community-driven projects, this might be seen as a disadvantage.
4. Performance Benchmarking: company’s marketing emphasizes its ability to handle over 50,000 transactions per second per node with sub-millisecond latency. If Evan’s experience, although substantial, did not involve managing systems with similar performance benchmarks or if he has not demonstrated comparable high-performance tuning skills, it could be a drawback.
5. Experience with Vendor-Agnostic Solutions: company’s solutions are designed to be vendor-agnostic and integrate with various cloud platforms and protocols. If Evan’s experience has been more closely tied to specific vendors or platforms, this might not align well with company’s requirement for a broad, vendor-agnostic approach.
6. Extensibility and Plugin Management: company’s platform is highly extensible with numerous out-of-the-box and custom plugins. If Evan’s experience does not demonstrate working with or managing a similarly extensive plugin ecosystem or if he lacks experience with customizable API management solutions, this could be a gap.
7. Automation and DevOps Practices: company emphasizes automation through declarative configuration and GitOps principles. If Evan’s experience with automation and DevOps practices does not specifically highlight these areas or if his previous roles involved more manual processes, it might be less aligned with company’s needs.
8. Enterprise-Grade Support and Services: company provides enterprise-grade support and services. If Evan’s background does not show experience in a high-touch support environment or managing enterprise-level customer support services, it might be a consideration.
9. Alignment with company’s Core Values: company places a strong emphasis on its core values, including being customer champions, owners, and explorers. If Evan’s previous roles do not clearly demonstrate alignment with these values or if his approach to leadership and team dynamics doesn’t fit with company’s culture, this could be a potential issue.

These points provide a nuanced view of potential reasons why Evan might not be the perfect fit for the company Gateway role, despite his considerable experience and achievements.

I addressed these concerns and demonstrated that I have substantial experience in the areas mentioned. With these qualifications in mind, I posed the ultimate question: Should we hire Evan?

To determine whether to hire Evan, consider the following:

Strengths:

1. Experience with High-Performance Systems: Evan has managed systems with over 5000 API requests per second and has significant experience with scalable architectures.
2. Leadership and Team Management: Proven ability to restructure and optimize global teams, enhancing collaboration and efficiency.
3. Technical Expertise: Extensive background in cloud technologies, Kubernetes, and compliance, with hands-on experience in automated testing and incident management.
4. Diverse Team Experience: Successfully led and supported diverse, geographically dispersed teams, aligning with company's global and inclusive culture.

Potential Concerns:

1. Alignment with company’s Specific Needs: Ensure Evan’s experience with API management and infrastructure aligns with company’s specific technology stack and challenges.
2. Fit with Company Culture: While Evan has demonstrated effective leadership and innovation, assess if his approach and values align closely with company’s core values and company culture.

Overall, Evan’s strong technical background, leadership skills, and experience with high-performance systems make him a strong candidate. However, confirming that his skills and values align with company’s specific needs and culture is crucial.

The LLM’s final recommendation was to proceed with the interview, highlighting that my strong technical background and leadership skills make me a strong candidate. Verifying that my skills and values align with the company’s needs and culture is essential.

The ultimate goal of interviews is to confirm experience and cultural fit. By addressing these concerns, I ensure a more targeted and effective presentation of my qualifications.

You have to let it all go, Neo. Fear, doubt, and disbelief. Free your mind.

In the competitive job market, simply submitting a standard resume often falls short of demonstrating your true potential. An adversarial approach, on the other hand, involves critically analyzing and challenging your own resume through an impartial lens, allowing you to present yourself in the best possible light.

By adopting this method, you effectively simulate the perspective of an objective evaluator, much like a third-party reviewer or an AI system. This adversarial approach requires you to anticipate and address potential criticisms or gaps in your resume before they are raised by recruiters or automated systems. This proactive strategy not only improves the overall quality of your resume but also ensures it is hyper-tailored to the specific requirements of each job.

Here’s how this approach enhances your resume:

1. Anticipating Objections: Just as an AI system might flag inconsistencies or gaps, this method forces you to scrutinize your resume for weaknesses. By addressing these potential issues beforehand, you strengthen your resume and preemptively counter any objections a recruiter might have.
2. Refining Details: An adversarial review pushes you to refine the details of your resume, ensuring that every section is optimized for relevance and impact. This meticulous attention to detail results in a higher quality resume that better aligns with job requirements.
3. Improving Alignment: By simulating an impartial review, you can better align your resume with the job description and required qualifications. This alignment enhances the likelihood that your resume will pass through initial AI screenings and attract the attention of human recruiters.
4. Enhancing Presentation: The adversarial approach helps you present your qualifications in the most compelling manner. It allows you to showcase your strengths and achievements in a way that clearly demonstrates your fit for the role, beyond what a standard resume might convey.

Ultimately, this adversarial approach transforms your resume from a mere list of qualifications into a powerful tool that effectively communicates why you are the ideal candidate. By engaging in this rigorous review process, you elevate the quality of your resume and increase your chances of standing out in a crowded job market.

You’re the One, Neo.

An LLM is a powerful tool for refining not just your resume, but also for crafting a compelling cover letter that addresses potential gaps. While your resume might reveal areas that don’t perfectly align with job requirements, a well-crafted cover letter can bridge those gaps.

Using an LLM, you can create a cover letter that acknowledges any shortcomings, highlights transferable skills, and showcases your enthusiasm for the role. It helps frame your experience to emphasize its relevance and align your values with the company’s mission.

Although many recruiters may not read cover letters closely and they are often seen as optional, a well-crafted one can still set you apart if requested. By proactively addressing shortcomings and emphasizing your strengths, an LLM can help make your application stronger and more compelling. This extra effort can make a difference in a competitive job market, even if the cover letter isn’t always the primary focus.

When applying to a job in the fintech sector, where I don't have direct experience but possess many transferable skills, an LLM crafted a tailored cover letter to bridge the gap:

Dear Hiring Manager,

I am excited to apply for the Engineering Manager, Billing Experience position at company. With a proven track record of managing high-performance engineering teams and developing scalable systems, I am eager to contribute to company’s mission of enhancing financial infrastructure and driving global economic growth.

In my role as Software Development Manager at Aylo, I led a team of 15 engineers responsible for critical infrastructure and complex revenue calculations. I successfully managed systems handling 5000 requests per second and supported over 140 million authenticated users daily. This experience has honed my skills in delivering scalable and reliable solutions, aligning closely with company’s goal of building secure and flexible billing systems.

At Aylo, I restructured the team to optimize workload distribution and promoted team members into leadership roles, reflecting my commitment to fostering high-performing teams and supporting their career growth. I implemented Agile and Kanban methodologies to improve project delivery and accuracy, which I believe aligns with company’s focus on driving high technical quality and impact. During my tenure at Guest Networks, I led a remote team across multiple countries, enhancing product performance and scalability through system rearchitecture and vendor hardware integrations. My hands-on experience with AWS, Docker, and continuous delivery processes will be valuable in building and scaling company’s revenue product offerings.

My role at Site2020 involved developing billing solutions for environments with variable connectivity, showcasing my ability to handle complex revenue systems and ensure compliance with evolving requirements. This experience aligns with the responsibilities of managing company’s billing infrastructure and integrating revenue systems.

My background in leading teams, optimizing systems, and handling critical infrastructure has equipped me with the skills necessary to drive company’s billing experience strategy and contribute to engineering-wide initiatives. I am particularly drawn to company’s innovative approach and the opportunity to work on high-impact solutions that support top enterprise use cases. Thank you for considering my application. I look forward to discussing how my experience and skills align with company’s needs and how I can contribute to your team’s success.

Sincerely,

Evan d’Entremont

In one case, for a company specializing in LLM chatbots, my cover letter literally included a link to ChatGPT explaining why I should get the job..

Overall, Evan’s blend of leadership experience, technical expertise, and focus on innovation makes him a compelling candidate for the Engineering Manager role at Ada. His background aligns well with the responsibilities and goals outlined in the job description, positioning him to effectively contribute to Ada’s continued success and growth.

This approach not only showcased my creativity but also leveraged technology to present a persuasive case for my candidacy.

Welcome to the real world.

The rise of AI in recruitment is creating a dynamic where job seekers and employers are increasingly engaged in an arms race of technological adaptation. As AI systems become more sophisticated in screening and evaluating candidates, job seekers must also leverage AI tools to enhance their applications. This ongoing competition means that those who can effectively use AI to optimize their resumes and align their profiles with job requirements will have a significant advantage. Navigating this evolving landscape requires not only understanding AI tools but also staying ahead in the race by continuously refining and adapting one's approach to job applications. Whether or not this competitive edge is the ultimate goal of AI-driven hiring, it’s clear that success now hinges on one's ability to adeptly use these technologies to stand out in a crowded job market.