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About This Role
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Summary
Cyber74, a New Charter Technologies operating company, is building a new practice focused on AI security — and we are looking for a Security / AI Cloud Engineer to help launch it. In this role, you will work at the intersection of cloud security and artificial intelligence, helping our clients adopt AI tools and platforms safely. You will configure and manage security controls across AI\-enabled environments, including data loss prevention policies, abuse alerting, and misconfiguration remediation. This is a greenfield opportunity to define a new service area within Cyber74, influence our methodology, and become one of the company's go\-to experts in AI security as clients increasingly integrate AI into their operations.
Primary Responsibilities
- Design, implement, and manage security controls for AI platforms and cloud environments used by Cyber74 clients (Microsoft 365 Copilot, Azure OpenAI, Google Workspace AI, and similar)
- Configure and tune Data Loss Prevention (DLP) policies to prevent sensitive data exposure through AI tools and integrations
- Develop and maintain alerting rules to detect abuse, anomalous behavior, and policy violations within AI\-enabled platforms
- Identify, remediate, and track security misconfigurations across AI and cloud environments using industry frameworks and tooling
- Conduct security assessments of client AI deployments to identify gaps, risks, and areas for hardening
- Collaborate with the vCISO and compliance teams to incorporate AI security considerations into broader client security programs
- Document findings, configurations, and procedures; produce clear reports for both technical and executive audiences
- Monitor the evolving AI security landscape and recommend new controls, tools, or policies as AI capabilities and threats develop
- Support pre\-sales and scoping conversations by contributing technical expertise to proposals and client discussions
Preferred Skills \& Experience
- 3\+ years of experience in cloud security, security engineering, or a related role
- Hands\-on experience with Microsoft 365 security tools (Defender, Purview/DLP, Conditional Access, Sentinel) or equivalent Google/AWS platforms
- Familiarity with AI platforms and their security surfaces: Microsoft Copilot, Azure OpenAI, ChatGPT Enterprise, Google Gemini, or similar
- Experience configuring DLP policies, CASB solutions, or similar data security controls in cloud environments
- Working knowledge of CSPM tools (Microsoft Defender for Cloud, Prisma Cloud, Wiz, or similar) for identifying misconfigurations
- Understanding of zero\-trust architecture principles and their application to AI workloads
- Relevant certifications preferred: AZ\-500, SC\-200, SC\-400, CCSP, or equivalent cloud/security certifications
- Strong documentation and communication skills; ability to explain complex security concepts to non\-technical stakeholders
- Salary range of $110k to $130k Dependent on Experience
Preferred Attributes
- Intellectually curious and energized by emerging technology; excited to build something new rather than maintain the status quo
- Comfortable operating with ambiguity in a greenfield role where processes are still being defined
- Collaborative and team\-oriented, able to work cross\-functionally with compliance, engineering, and client\-facing teams
- Strong problem\-solving skills with a proactive approach to identifying risks before they become incidents
- Passion for AI and security; keeps up with industry news, emerging threats, and evolving best practices
- Client\-focused mindset with the ability to build trusted relationships and communicate findings with clarity and credibility
Who We are:
At New Charter, we’re building a caliber of business the IT industry hasn’t yet seen. We are serving small\-to\-medium sized businesses in 10\+ industries across North America, and we deliver best\-in\-class technology solutions to propel our clients into the digital world.
At New Charter Technologies, we’re investing in our people – through growth and learning initiatives, employee benefits, company innovation, and more. We are constantly seeking a diverse candidate backgrounds and perspectives to amplify inclusive hiring practices for each job opening. Our partner companies have career paths for many different role types, whether you want to be deeply technical or whiteboarding with clients, and we are committed to developing fulfilling career paths for all contributors at New Charter Technologies. ( *Please note: Every application submitted through Workday is reviewed by a real person, not an AI. We value your time and take each submission seriously.)*
Our teams are dedicated to pioneering breakthrough technologies, disruptive solutions, and transformative strategies. We’re the architects of change, fostering an environment where bold ideas take flight, and creativity knows no bounds. At New Charter Technologies, we’ve embraced the idea that every individual brings something special to the table. Our foundation is based on the belief that each team member plays a crucial role in our collective success.
Ready to be part of a dynamic and supportive community where your unique skills and personality shine? We’re on a mission to make a difference, and we want you to be part of the story. Let’s transform the world together and build a career that’s as unique as you are!
We are looking for driven and passionate people who are excited to work in an incredibly rewarding environment. So, if you are ready to learn, be inspired, solve problems, and grow professionally, apply today! Learn more here: Why New Charter .
New Charter Technologies *is committ* *e* *d to cr* *e* *ating an inclusiv* *e* *e* *nvironm* *e* *nt and is proud to b* *e* *an* *e* *qual opportunity* *e* *mploy* *er. New Charter re* *cruits,* *e* *mploys, trains, comp* *e* *nsat* *e* *s, and promot* *e* *s r* *e* *gardl* *e* *ss of rac* *e* *, color, r* *e* *ligion, s* *e* *x, s* *e* *xual ori* *e* *ntation, g* *e* *nd* *e* *r id* *e* *ntity, national origin, v* *e* *t* *eran, or disability status.*
Salary Context
This $110K-$130K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At New Charter Technologies, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($120K) sits 44% below the category median. Disclosed range: $110K to $130K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
New Charter Technologies AI Hiring
New Charter Technologies has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span CO, US, CT, US. Compensation range: $120K - $130K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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