AI Security Engineer

Description Position Details:

Job Title:

AI Security Engineer

Job Type: Full-time

Location:

Remote, MD

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.

• 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.

• 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.

• Integrate Entra  / 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.

• 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.

• 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.

• 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.

• 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.

• Azure (Azure OpenAI, AI Studio, AKS, Key Vault, Entra , Defender), Microsoft Purview, and M365 Copilot governance.
• Experience with AWS (Bedrock, Sage Maker, KMS) or GCP Vertex AI.

• 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).

• OAuth/OIDC, SAML, SCIM, RBAC/ABAC; secrets management via Key Vault, Parameter Store, or Vault.

• Encryption, tokenization, redaction, differential privacy basics, DLP-based PII/PHI detection.
• Experience with data classification, retention, and lineage.

• STRIDE threat modeling, secure coding, dependency scanning, secret scanning, SAST/DAST.
• CI/CD for AI apps (Git Hub Actions/Azure Dev Ops), IaC (Bicep/Terraform), policy-as-code (OPA/Conftest/Azure Policy).

• Logging with Azure Monitor/Sentinel, tracing, metrics, and automated AI evaluation pipelines integrated with SIEM/SOAR.

• Working knowledge of NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10, and public sector controls.
• Experience documenting controls, audits, and risk assessments.

• Proficiency in Python or Type Script/Node.js.
• Experience with agent/orchestration frameworks (Lang Chain, Semantic Kernel, Guidance, DSPy).

• 5-8+ years in application/cloud security with 2+…