AI Security Engineer

Dynanet

Elkridge, Northern (MD, KY)

Hybrid

USD 130,000 - 190,000

Full time

4 days ago
Be an early applicant
Application generator

A complete application in a minute — tailored resume and cover letter, ready to send.

Get past ATS filters

Job summary

Dynanet in Maryland is seeking an experienced Security Architect to lead AI security across cloud and hybrid deployments. You will craft secure architectures for LLM/agent workloads, implement guardrails, and enforce enterprise policies with robust identity and data protection controls.

Responsibilities include embedding secure SDLC, aligning with NIST AI RMF, and building automation for monitoring, logging, and incident response.

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Cybersecurity, or equivalent.
  • 5–8+ years in application/cloud security, with 2+ years in AI/ML security.
  • Experience enabling enterprise AI use cases or AI agents in regulated environments.
  • Familiarity with Microsoft Copilot for M365 governance and Purview.
  • Experience with AI red teaming and building evaluation harnesses.

Responsibilities

  • Design secure reference architectures for AI workloads across Azure, AWS, or hybrid environments.
  • Implement runtime guardrails including prompt injection defenses and content filtering.
  • Codify enterprise policies into enforceable controls via middleware, gateways, and policy engines.
  • Integrate identity and access controls (Entra ID, OAuth/OIDC, RBAC/ABAC) and data protection measures.
  • Embed secure SDLC practices for AI, including SAST/DAST and dependency scanning.
  • Operationalize governance frameworks (NIST AI RMF, ISO/IEC 27001) and maintain audit trails.

Skills

Azure OpenAI
Azure AD
RBAC ABAC
PII detection
Data protection
SAST DAST
Python
TypeScript
LangChain
Security engineering

Education

Bachelor's degree in CS/Engineering or Cybersecurity

Tools

Cosmos DB
pgvector
FAISS
Pinecone
Weaviate
KMS
Key Vault

Job description

Dynanet started with a focus on IT infrastructure and operations, helping organizations enhance their networks and overcome the limitations of 1990s technology. From strengthening communication channels to introducing innovative ways to collaborate and share information, Dynanet played a crucial role in shaping the early stages of digital transformation. The company’s efforts helped organizations build the very fabric of connectivity that now powers our modern world. Over the last three decades, Dynanet has grown into a trusted partner for organizations looking to innovate boldly and transform seamlessly. While technology continues to evolve and unlock new opportunities, for nearly 30 years, Dynanet remains committed to delivering cutting-edge solutions that drive lasting change for its customers. Through agility, foresight, and an unwavering dedication to excellence, Dynanet continues to empower organizations to thrive in a rapidly changing digital landscape. Our story is more than just a story of technology – it’s a story of vision, growth, and transformation that has shaped the past and continues to pave the way for the future.

Security Architecture for AI Workloads
  • Design reference architectures for secure LLM/AI agent deployments across Azure, AWS, or hybrid environments.
  • Establish defense-in-depth controls for model endpoints, vector databases, prompt routing, tools/plugins, and orchestration layers.
Guardrails & Policy Enforcement
  • Implement runtime guardrails including prompt injection defenses, output content filtering, PII detection/redaction, jailbreak prevention, and tool use restrictions.
  • Codify enterprise policies (acceptable use, data residency, retention, secrets handling) into enforceable controls through middleware, gateways, and policy engines.
Identity, Access & Data Protection
  • Integrate Entra ID / Azure AD, OAuth/OIDC, and RBAC/ABAC models.
  • Apply data security measures including DLP, encryption, key management/HSM, tokenization, and fine-grained data access for RAG pipelines.
Secure SDLC for AI
  • Embed threat modeling, secure coding, dependency scanning, secret scanning, and SAST/DAST into AI app pipelines.
  • Define AI-specific code review checklists for prompt templates, tool bindings, and agent plans.
Risk, Governance & Compliance
  • Operationalize NIST AI RMF, ISO/IEC 27001 & 42001, SOC 2; align with FedRAMP, FISMA, NIST 800-53, and agency-specific controls.
  • Maintain model cards, data lineage, evaluation reports, and audit trails for AI decisions and tool calls.
AI Red Teaming & Evaluation
  • Design adversarial tests for jailbreaks, prompt injections, data exfiltration attempts, and toxic outputs.
  • Build automated evaluation harnesses and metrics such as hallucination rates, sensitive content occurrence, and tool misuse rates.
  • Establish observability for AI systems including privacy-aware logging, policy hits, model drift detection, cost governance, and anomalies.
  • Define playbooks for AI incidents involving unsafe outputs, data leakage, compromised tools, or model endpoint abuse.
Stakeholder Enablement
  • Partner with Product and Engineering teams to safely accelerate new AI use cases.
  • Provide training and guidance on responsible AI, secure agent design, and safe prompt engineering.
Required Professional Skills:
  • Azure (Azure OpenAI, AI Studio, AKS, Key Vault, Entra ID, Defender), Microsoft Purview, and M365 Copilot governance.
  • Experience with AWS (Bedrock, SageMaker, KMS) or GCP Vertex AI.
LLM/Agent Security
  • Hands-on guardrail implementation including content filters, safety classifiers, prompt injection defenses, jailbreak prevention, and tool whitelisting.
  • Securing RAG pipelines and vector databases (Cosmos DB + pgvector/FAISS, Pinecone, Weaviate).
Identity & Access
  • OAuth/OIDC, SAML, SCIM, RBAC/ABAC; secrets management via Key Vault, Parameter Store, or Vault.
Data Security
  • Encryption, tokenization, redaction, differential privacy basics, DLP-based PII/PHI detection.
  • Experience with data classification, retention, and lineage.
Application Security & DevSecOps
  • STRIDE threat modeling, secure coding, dependency scanning, secret scanning, SAST/DAST.
Observability & Incident Response
  • Logging with Azure Monitor/Sentinel, tracing, metrics, and automated AI evaluation pipelines integrated with SIEM/SOAR.
Compliance & Governance
  • Working knowledge of NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10, and public sector controls.
  • Experience documenting controls, audits, and risk assessments.
Programming & Frameworks
  • Proficiency in Python or TypeScript/Node.js.
  • Experience with agent/orchestration frameworks (LangChain, Semantic Kernel, Guidance, DSPy).
Preferred Professional Skills:
  • 5–8+ years in application/cloud security with 2+ years in AI/ML or LLM security.
  • Experience enabling enterprise AI use cases or AI agents in regulated environments.
  • Familiarity with Microsoft Copilot for M365 governance and Microsoft Purview.
  • Experience with AI red teaming and building evaluation harnesses.
  • Exposure to privacy regulations (HIPAA, GLBA, GDPR/CCPA) and public-sector compliance.
  • Contributions to security frameworks or open-source guardrail tools
Dynanet Team Requirements and Expectations:
  • Possess Strong written and verbal communication skills.
  • Highly organized with the ability to prioritize, balance, and effectively advance multiple competing priorities in a high-volume, fast-paced environment.
  • Ability to interact in a professional and collaborative manner with fellow Dynanet Teammates and the clients, and business partners that we work with.
  • Ability and desire to challenge and educate yourself to support and advance IT services delivery in the Federal agencies we serve.
  • Excellent judgment and creative problem-solving skills.
  • Respond to team member and client requests via email, MS teams, or other communication means during core business hours.
  • Active listening skills to understand clients' needs, and collaboration skills to work with other developers and designers.
Education/Experience Requirements:
  • Relevant degree in Computer Science, Engineering, Cybersecurity, or equivalent experience.
Nice to Have Certs
  • CISSP, CCSP, Azure Security Engineer (AZ-500), GIAC (GWEB/GWAPT/GXPN), OSCP.
  • Azure AI Engineer (AI-102), Azure Solutions Architect (AZ-305), AWS Security Specialty.
  • CISA, ISO 27001 Lead Implementer, Responsible AI certifications
Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Senior AI Security Engineer
Senior AI Security Engineer

Plaster Group, LLC • Seattle (WA)

On-site
USD 150,000 - 190,000
Security Architect - AI AppSec
Security Architect - AI AppSec

Sovereign Care Services LLP • Chicago (IL)

On-site
USD 110,000 - 150,000
401(k)
Employee discounts
Opportunity for advancement
+3
Senior Cybersecurity Engineer
Senior Cybersecurity Engineer

Leeds Professional Resources • Chicago (IL)

On-site
USD 110,000 - 150,000
Principal Engineer – AI Security
Principal Engineer – AI Security

Jobtailor • Brooklyn Park (MN)

On-site
USD 180,000 - 260,000
Stock options
Hybrid C2C Role – Fort Worth, TX | AI Security Architect With Cybersecurity
Hybrid C2C Role – Fort Worth, TX | AI Security Architect With Cybersecurity

Tech Mirrors • Fort Worth (TX)

On-site
USD 89,000 - 134,000
Lead Engineer – AI Security
Lead Engineer – AI Security

Jobtailor • Brooklyn Park (MN)

On-site
USD 120,000 - 150,000
Security Architect AI AppSec
Security Architect AI AppSec

Sovereign Care Services • Chicago (IL)

On-site
USD 110,000 - 150,000
401(k)
Employee discounts
Opportunity for advancement
+2
AI Security Specialist
AI Security Specialist

Milbank LLP • New York (NY)

On-site
USD 140,000 - 180,000
AI Security Specialist
AI Security Specialist

MAP SSG • New York (NY)

On-site
USD 140,000 - 180,000
AI Platform Security Engineer
AI Platform Security Engineer

Kai • San Jose (CA)

On-site
USD 180,000 - 240,000