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About This Role
Who We Are:
Ready to make a real impact in cybersecurity? At Critical Start, we're not just protecting organizations; we're redefining how it's done. We're a team united by an inspiring purpose: to stop breaches, simplify security, and shape the future of cyber defense. If you're passionate about cutting\-edge technology, thrive in a collaborative environment, and want your work to truly matter, you've found your home.
We deliver 24x7 AI\-accelerated, human\-validated detection, investigation, and response across IT and OT. This means we cut through the noise, investigate real threats, and take trusted, SLA\-backed action—all powered by the brightest minds and the latest AI. Since 2012, we've been helping organizations outpace evolving attacks with faster response, fewer escalations, and measurable risk reduction.
Innovation isn't just a buzzword here; it's our DNA. We pioneered the first MOBILESOC app for on\-the\-go detection and response, infused AI into automated alert resolution to eliminate noise, and slashed investigation time by an astounding 99\.3%. We're transforming how security teams work, and you could be a part of it. From AI\-assisted triage to analyst copilots that elevate human expertise, we combine machine intelligence with human judgment to deliver outcomes our customer’s trust.
If you're looking for a high\-trust, high\-impact team where your ideas are amplified by AI and valued by colleagues and customers alike, Critical Start is the place for you. Come build the future of cybersecurity with us.
Want to hear from our team? Watch these videos to gain insights into life at Critical Start or check out our Glassdoor reviews for an inside look.
Who You Are:
We are seeking a technically fluent, editorially sharp AI Content Engineer to join our Marketing team. This is a true hybrid role, equal parts content practitioner and AI systems builder. This is designed for someone who is just as comfortable structuring a content model as they are commissioning a great piece of writing.
You will own both the craft and the infrastructure: developing compelling cybersecurity content while also building and optimizing the AI\-powered tools, agents, and workflows that make our content operation faster, smarter, and more scalable.
The ideal candidate brings cybersecurity domain knowledge, strong editorial instincts, and hands\-on experience implementing AI tools in a production content environment. You understand how to translate complex security concepts — including Managed Detection and Response (MDR), SOC operations, AI/ML, and incident response — into clear, compelling narratives for both technical and executive audiences. And you know how to build the systems that make producing that content repeatable at scale.
This role sits at the intersection of content strategy, editorial execution, and marketing technology and requires genuine depth on both sides.
What You Will Be Doing?:
- AI\-Assisted Content Creation \& Development: Use AI\-powered content tools to generate first drafts of cybersecurity content and refine them through expert editing and quality assurance. Develop and manage technical and promotional materials including:
+ White papers
+ Product sheets
+ Technical briefs
+ Battle cards
+ Data sheets
+ Customer case studies
+ Security reports
+ Executive thought leadershi
- Create engaging content for digital channels, including:
+ Websites and landing pages
+ Blog articles and thought leadership
+ Social media campaigns
+ Email marketing content
+ Video scripts and multimedia assets
Ensure all content is accurate, technically sound, and aligned with brand voice and messaging standards.
*
- Technical Editing \& AI Output Validation: Review and validate AI\-generated content to ensure technical accuracy, clarity, and credibility; Translate complex cybersecurity topics—including MDR operations, threat detection, SIEM, EDR/XDR, and incident response—into clear and accessible language for diverse audiences; Collaborate with cybersecurity SMEs, SOC analysts, product teams, and sales engineers to validate technical content and strengthen thought leadership positioning.
- Visual \& Multimedia Content Coordination: Coordinate with designers or leverage AI design tools to develop:
+ Slides and presentations
+ Infographics
+ Data visualizations
+ Video scripts and multimedia content
Ensure visual elements accurately represent security architecture, MDR capabilities, and threat intelligence insights while maintaining brand consistency.
*
- AI Content Operations \& Workflow Management: Design and manage AI\-assisted content workflows to improve production speed while maintaining editorial quality; Maintain editorial calendars and ensure timely delivery of marketing materials; Continuously review and optimize existing content to ensure accuracy, relevance, and performance; Measure content performance and provide data\-driven recommendations for optimization and improvement.
What You Will Bring?:
Required Qualifications:
- Bachelor’s degree in Marketing, Communications, English, Journalism, Technical Writing, or a related field.
- 5\+ years of experience in content marketing, technical writing, editorial management, or a related role.
- Experience in creating technical and promotional content within cybersecurity, MDR, or IT security industries.
- Experience using AI tools for content generation and workflow optimization (e.g., Claude, Jasper, generative AI platforms, AI writing tools).
- Exceptional writing, editing, storytelling, and proofreading skills with strong attention to technical accuracy.
- Ability to evaluate and refine AI\-generated content to ensure clarity, credibility, and technical precision.
- Proficiency in grammar, syntax, and style guidelines (e.g., AP Style, Chicago Manual of Style).
- Experience with content management systems (CMS) and digital publishing platforms.
- Understanding of SEO best practices and web content optimization.
- Strong project management skills with the ability to manage multiple priorities and deadlines in a fast\-paced environment.
Desired Qualifications:
- Strong understanding of cybersecurity fundamentals and MDR concepts, including:
+ SIEM
+ SOC Operations
+ EDR/XDR
+ Threat Detection
+ Incident Response
- Experience with Adobe Creative Suite, Canva, or similar design tools.
- Familiarity with marketing automation platforms such as HubSpot or Marketo.
- Experience creating data visualizations, infographics, and multimedia content.
- Understanding of video production and multimedia storytelling.
- Certification in technical writing, content marketing, or AI\-driven content strategy.
What It's Like Working Here:
Imagine a dynamic, enjoyable, and rewarding work environment. We are professionals, and the work we do holds immense significance, like saving our customers from potential disasters. However, we believe in not taking ourselves too seriously.
Prefer a casual dress code every day? No problem, as we find comfort enhances our thinking.
Our workplace in Plano, TX offers open offices, collaborative meeting spaces, phone rooms, and wellness rooms. In the breakroom, friendly competition arises with games like ping\-pong, bubble hockey machine, foosball, or the gaming machine. What harm does a little healthy competition among friends do? What does our Compensation and Benefits package entail?* Competitive salary with bonus potential
- Comprehensive health benefits with generous employer contributions for medical, dental, and vision
- Additional Ancillary Benefits offered at 100% employee contribution
- Unlimited PTO (Paid Time Off) policy
- Paid Parental and Military Leave
- Dental and Vision Plan
- Employer\-provided Life Insurance, Long\-Term Disability, and Short\-Term Disability coverage
- Additional Voluntary Life Insurance coverage
- 401(k) Plan with Matching Program
- Mines Employee Assistance Program
- Monthly Wellness Initiatives
- Optional Pet Benefits Discount Plan
We prioritize your privacy and security. Please note that Critical Start will never request financial information or sensitive personal data during the interview process. If you encounter any suspicious requests, do not respond and contact us directly at recruiting@criticalstart.com. Thank you for helping us maintain a safe and trustworthy hiring experience.
Critical Start welcomes people from all backgrounds and walks of life. One of our core values is to “Do what’s best for our employees,” and that starts with the hiring process by finding the best candidates and providing an environment that upholds equal employment opportunities for all employees and applicants, strictly prohibiting any form of discrimination or harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
This policy encompasses all aspects of employment, including recruitment, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Mental and Physical Requirements
It's important to note that specific physical and mental requirements may vary depending on the nature of the office job, organization, and individual responsibilities. Physical:* Stationary position for extended periods of time.
- Constantly operate a computer.
- Occasionally you may be required to move equipment or other items up to 20 lbs.
- The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.
Mental:* Must be able to apply established protocols in a timely manner.
- Make timely decisions in the context of workflow.
- Ability to complete tasks and perform in situations requiring speed deadlines, or productivity quota.
- Ability to work effectively and efficiently in high stress situations.
- Ability to simultaneously address multiple complex problems.
For positions that can or will be performed, in whole or in part, remotely within the U.S., range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, experience, performance in the role and potential for revenue generation (sales roles only). Compensation:
The total compensation range (base) being offered for this role is \[$80,000 \- $100,000 USD]. Additional Compensation:
This role is eligible for the following: performance\-based bonus compensation. Employment Benefits:
Comprehensive health benefits with generous employer contributions for medical, dental, and vision, unlimited PTO (Paid Time Off) policy, paid Parental and Military Leave, dental and vision plan, Employer\-provided Life Insurance (up to $100K coverage), Long\-Term Disability, and Short\-Term Disability coverage, 401(k) Plan with Matching Program, 24/7/365 availability of Employee Assistance Program. Application Deadline:
The application deadline for this position is May 31, 2026\. How to Apply:
Interested candidates are invited to visit our career site and apply for the position: https://www.criticalstart.com/careers/
\#LI\-CV1
\#LI\-remote
Salary Context
This $80K-$100K range is below the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Critical Start, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($90K) sits 46% below the category median. Disclosed range: $80K to $100K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Critical Start AI Hiring
Critical Start has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Washington, DC, US. Compensation range: $100K - $100K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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.
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