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About This Role
WHO WE ARE
Come join the company at the center of how the world adopts AI securely. Cyera’s mission is to give enterprises the confidence to embrace AI safely — deciding exactly what it can see and do as it reaches deeper into the business. We started by solving the hardest problem in data security: finding and securing data faster and more precisely than anyone thought possible. That foundation is now the essential AI trust infrastructure for the Fortune 1000\. We’re hiring mission\-driven talent to put those leaders at the center of our story.
THE OPPORTUNITY
Cyera is looking for a Principal AI Technologist to help lead our AI security technical motion across strategic customers, field teams, and market\-facing initiatives.
This is a senior, field\-facing role for a highly technical leader who combines deep AI and security expertise with strong customer engagement skills, technical storytelling, and cross\-functional influence. You will work at the intersection of customers, Sales, Sales Engineering, Field CTO, Product, Engineering, PMM, and the Field CISO team to help shape how Cyera sells, demonstrates, and scales its AI security leadership.
As a Principal AI Technologist, you will serve as a senior subject matter expert on AI security in customer and prospect engagements. You will help customers understand AI\-related risk, governance, posture, and data security challenges; support strategic opportunities that require deeper AI expertise; and help translate market needs into product insight, technical messaging, enablement, and thought leadership.
This role is close to the Field CTO function in seniority and impact, with greater emphasis on domain depth, technical execution, and repeatable field leverage across AI\-focused opportunities.
RESPONSIBILITIES:
AI Security Technical Leadership
Serve as a senior AI security subject matter expert for customers, prospects, partners, and internal teams.
Help articulate Cyera’s AI security vision, platform value, and differentiated technical approach in customer\-facing engagements.
Engage in high\-impact opportunities where deeper AI expertise can materially improve technical credibility, positioning, or deal quality.
Partner with Field CTOs on the largest and most strategic engagements, while also independently leading AI\-focused technical workstreams across the field.
Strategic Customer Engagement
Work directly with customer technical and executive stakeholders to understand AI initiatives, governance challenges, risk posture, and architectural requirements.
Lead AI\-focused discovery sessions, technical deep dives, workshops, and strategic POV design.
Support conversations involving AI governance, model usage, sensitive data exposure, data flows, access controls, posture management, and emerging AI security requirements.
Help elevate customer conversations from narrow use cases to broader platform and strategic outcomes.
POVs, Demos, and Technical Execution
Design and deliver compelling AI security demos, solution narratives, and proof\-of\-value approaches that align with customer priorities.
Improve the technical rigor and repeatability of AI\-focused POVs and evaluations.
Develop reusable technical patterns, reference architectures, and playbooks for common AI security use cases.
Help the field ask better questions, identify stronger success criteria, and position Cyera more effectively in AI\-related opportunities.
Product and Engineering Influence
Bring structured field insight back into Product and Engineering based on strategic customer engagements.
Identify product gaps, recurring friction points, emerging market needs, and high\-value requirements related to AI security.
Help pressure\-test roadmap themes and technical direction based on direct customer feedback.
Act as a high\-signal liaison between the field and internal teams on AI security priorities.
PMM, Messaging, and Content
Partner closely with PMM on AI security messaging, positioning, launches, and technical narrative.
Act as a stakeholder in internal and public\-facing content creation, including blogs, webinars, decks, whitepapers, and solution briefs.
Help ensure Cyera’s AI security messaging stands up to scrutiny from technical buyers, practitioners, and industry experts.
Contribute to clear, credible, differentiated technical storytelling across customer\-facing materials.
Enablement and Thought Leadership
Help uplevel the field’s AI security fluency across Sales, SEs, and partner teams.
Build or contribute to enablement materials, playbooks, workshops, and technical talk tracks.
Represent Cyera at customer events, webinars, company events, and industry conferences as a technical voice on AI security.
Partner with the Field CISO team and broader GTM organization to scale Cyera’s thought leadership and visibility in the market.
Requirements:
REQUIRED QUALIFICATIONS:
Significant experience in senior technical roles such as Principal Technologist, Principal Solutions Architect, AI Security Architect, Distinguished Sales Engineer, Field Architect, or similar.
Strong customer\-facing experience in cybersecurity, cloud security, data security, AI security, or adjacent domains.
Deep understanding of modern AI and GenAI environments, including enterprise AI adoption patterns, governance challenges, data exposure risks, and security controls.
Strong understanding of areas such as data security, DSPM, DLP, IAM, cloud security, AI application risk, model and data governance, and security architecture.
Experience engaging with both technical practitioners and senior stakeholders in complex enterprise environments.
Ability to turn complex technical concepts into clear business and technical value for customers.
Proven ability to influence Product, PMM, and technical strategy through field insight and pattern recognition.
Strong written and verbal communication skills, including presentations, workshops, and technical content review.
Experience creating demos, POV strategies, technical assets, or enablement materials.
Comfort operating in a fast\-paced, high\-growth environment with cross\-functional ambiguity.
Preferred Qualifications
Experience working with enterprise AI initiatives, AI governance programs, or AI security use cases in the field.
Background in data security, cloud security, AI security, DSPM, DLP, posture management, or related cybersecurity categories.
Familiarity with enterprise AI platforms and cloud environments such as AWS, Azure, Google Cloud, Microsoft 365, and modern SaaS ecosystems.
Experience working in or with high\-growth startups.
Ability to travel as needed.
COMPENSATION INFORMATION:
Compensation Range: $250,000\-$300,000\.
The range represents total compensation, and may include incentive for sales roles, equity or benefits, as applicable.
This compensation range represents Cyera’s good faith and reasonable estimate of the range of possible compensation for this role at the time of posting, and Cyera may ultimately pay more or less than the posted range. The final salary for this position will be determined in Cyera’s sole discretion, consistent with applicable law, and based on a variety of factors, including but not limited to the employee’s work experience, skills, and qualifications for the role, as well as the needs of Cyera’s business and other operational considerations.
Final compensation will vary based on seniority and relevance of experience, location, and position requirements.
This role may be eligible for potential merit increases based on factors such as individual or company performance, time in role, and other discretionary factors. In addition to a standard benefits and equity package, we offer a generous salary. Final compensation will vary based on seniority and relevance of experience, location, and position requirements.
This role may be eligible for potential merit increases based on factors such as individual or company performance, time in role, and other discretionary factors.
BENEFITS \- Why Cyera?
Ability to work remotely, with office setup reimbursement
Unlimited PTO
Paid holidays and sick time
Health, vision, and dental insurance
Life, short and long\-term disability insurance
Salary Context
This $250K-$300K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Cyera, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($275K) sits 26% above the category median. Disclosed range: $250K to $300K.
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.
Cyera AI Hiring
Cyera has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $300K - $300K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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 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).
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 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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