Hire AI Security Engineers | TeamStation AI

As AI systems become more powerful and integrated into critical business processes, they also become a major target for new types of attacks. Our AI Security Engineers are experts in identifying and mitigating these emerging threats. We provide talent vetted for their expertise in prompt injection defense, data privacy in RAG pipelines, and securing the entire AI/ML supply chain.

Is your LLM application vulnerable to prompt injection attacks?

The Problem

A malicious user can craft an input that hijacks the LLM, causing it to ignore its original instructions and perform unintended actions, such as revealing sensitive information or executing harmful commands. This is a critical vulnerability for any public-facing LLM application.

The TeamStation AI Solution

Our AI Security Engineers are experts in prompt injection defense. They are vetted on their ability to implement multiple layers of protection, including input filtering, instruction defense, and output monitoring, to detect and block these attacks.

Proof: Robust defense against OWASP Top 10 for LLMs.
Does your RAG pipeline leak sensitive data?

The Problem

If your RAG system retrieves and presents information from documents with different access levels, a user might trick the LLM into revealing confidential data they are not authorized to see, creating a massive data breach risk.

The TeamStation AI Solution

We hire experts in secure RAG design. They can implement access control at the retrieval stage, ensuring that the documents fetched to provide context respect the user's permissions. This prevents the LLM from ever seeing, and therefore leaking, unauthorized information.

Proof: Secure, permission-aware retrieval in RAG systems.

How We Measure Seniority: From L1 to L4 Certified Expert

We don't just match keywords; we measure cognitive ability. Our Axiom Cortex™ engine evaluates every candidate against a 44-point psychometric and technical framework to precisely map their seniority and predict their success on your team. This data-driven approach allows for transparent, value-based pricing.

L1 Proficient

Guided Contributor

Contributes on component-level tasks within the AI Security Engineer domain. Foundational knowledge and learning agility are validated.

Evaluation Focus

Axiom Cortex™ validates core competencies via correctness, method clarity, and fluency scoring. We ensure they can reliably execute assigned tasks.

$20 /hour

$3,460/mo · $41,520/yr

± $5 USD

L2 Mid-Level

Independent Feature Owner

Independently ships features and services in the AI Security Engineer space, handling ambiguity with minimal supervision.

Evaluation Focus

We assess their mental model accuracy and problem-solving via composite scores and role-level normalization. They can own features end-to-end.

$30 / hour

$5,190/mo · $62,280/yr

± $5 USD

L3 Senior

Leads Complex Projects

Leads cross-component projects, raises standards, and provides mentorship within the AI Security Engineer discipline.

Evaluation Focus

Axiom Cortex™ measures their system design skills and architectural instinct specific to the AI Security Engineer domain via trait synthesis and semantic alignment scoring. They are force-multipliers.

$40 / hour

$6,920/mo · $83,040/yr

± $5 USD

L4 Expert

Org-Level Architect

Sets architecture and technical strategy for AI Security Engineer across teams, solving your most complex business problems.

Evaluation Focus

We validate their ability to make critical trade-offs related to the AI Security Engineer domain via utility-optimized decision gates and multi-objective analysis. They drive innovation at an organizational level.

$50 / hour

$8,650/mo · $103,800/yr

± $10 USD

Pricing estimates are calculated using the U.S. standard of 173 workable hours per month, which represents the realistic full-time workload after adjusting for federal holidays, paid time off (PTO), and sick leave.

Core Competencies We Validate for AI Security Engineer

LLM Application Security (OWASP Top 10 for LLMs)
Prompt Injection Defense Mechanisms
Data Privacy and Security in RAG Systems
Secure AI/ML Supply Chain (Model Provenance)
Adversarial Attack and Red Teaming Simulation

Our Technical Analysis for AI Security Engineer

Candidates are tasked with performing a security audit of an existing LLM application. They must identify potential vulnerabilities, including prompt injection and data leakage risks, and demonstrate how to exploit them. The critical assessment is their ability to then design and implement effective countermeasures to secure the application.

Related Specializations

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