Senior AI Security Lead — Remote

DataSpring; Washington (District of Columbia); On-site; USD 180,000 - 195,000; Full time

Benefits offered by this job

Medical, Dental, and Vision coverage

401(k) with company contributions and

Paid parental leave

Tuition assistance

Generous paid time off

Job summary

DataSpring is seeking a Senior AI Security Engineer to secure AI-driven technology across model configuration, prompt pipelines, and data ingestion. You will design security controls, embed security into build processes, and partner with engineering and data teams. This fully remote, exempt role reports to the Sr.

Director, Security Architecture and Operations. You will lead threat modeling, secure architecture, and guard agency-level security for multi-agent systems, ensuring least-privilege

Qualifications

• 8+ years of progressive information security experience across architecture, application security, identity, and data domains.
• Hands-on use of Claude for application development, including system prompt design, tool-use configuration, and multi-agent orchestration.
• Experience with the Model Context Protocol (MCP) ecosystem and securing MCP server deployments.
• Red team or adversarial AI testing experience: model evasion, adversarial examples, jailbreak research.
• Background in a regulated industry with data sensitivity requirements, healthcare a plus.
• Contributions to AI security open-source projects, published research, or conference presentations (DEF CON AI Village, Black Hat, NeurIPS).
• Demonstrated success securing AI/ML systems, LLM applications, or agentic AI platforms in a production environment.
• Demonstrated experience building or securing applications developed substantially through LLM-assisted code generation (Claude, Copilot, Cursor, or equivalent).
• Cloud-native security experience on at least one major provider (AWS, Azure, GCP), including IAM policy design, network segmentation, and secrets management.
• Demonstrated success automating adversarial testing infrastructure include jailbreak suites, prompt injection harnesses, and regression pipelines tied to model and prompt changes.
• Relevant certifications: CISSP, CCSP, OSCP, AWS/Azure Security Specialty, or emerging AI security credentials.

Responsibilities

• Threat modeling and risk assessment: Lead threat modeling for AI capabilities, agentic features, and integrations.
• Maintain a living threat model aligned to OWASP Top 10 for LLMs, MITRE ATLAS, and NIST AI RMF, and translate findings into prioritized, actionable controls.
• Secure architecture: Own and maintain the AI security reference architecture covering model hosting, orchestration, tool use, MCP server deployments, and observability.
• Establish security patterns for new capabilities before they reach production.
• AI model and pipeline security: Evaluate foundation models for data-leakage risk and supply-chain provenance.
• Harden prompt pipelines against injection, jailbreaking, and context poisoning.
• Secure fine-tuning pipelines, RAG architectures, and embedding stores with appropriate access controls and poisoning detection.
• Agentic AI security: Define trust boundaries, tool call authorization, privilege scoping, and human-in-the-loop escalation policies for multi-agent systems.
• Ensure agents operate under least-privilege identities with revocable, short-lived credentials.
• AI-generated code and build security: Establish review, testing, and gating processes for AI-generated code across frontend, backend, IaC, and CI/CD.
• Embed security requirements and policy-as-code checks directly into Claude system prompts and project instructions used for development.
• Enforce SCA/SBOM generation, dependency allowlisting, and secrets management for all LLM-driven build outputs.
• Identity and access management: Define and enforce identity patterns for both human and non-human (agent) identities.
• Apply zero-trust principles to all model API calls, vector store queries, and external tool invocations.
• Every request must be authenticated, authorized, and logged.
• Architect OAuth/OIDC delegation patterns for agentic flows with bounded scopes and session limits.
• Data protection and ETL security: Classify and control data flowing into LLM context windows, vector databases, and training pipelines.
• Secure ETL and ingestion pipelines against poisoning and schema drift.
• Enforce masking, tokenization, and access controls to prevent regulated data (PII, PHI, PCI) from appearing in model inputs, outputs, or logs.
• Extend DLP coverage to LLM prompt submissions and completions.
• Detection, monitoring, and response: Instrument AI infrastructure with behavioral telemetry.
• Write detection rules for prompt injection attempts, anomalous agent behavior, and data exfiltration through LLMs.
• Serve as SME for AI-related security incidents, including model abuse, pipeline compromise, and agentic runaway actions.
• Compliance and audit: Support SOC 2, HIPAA, ISO 27001, and NIST AI RMF compliance as applied to AI systems.
• Maintain control mappings, evidence, and audit documentation.
• Evaluate and deploy AI-specific security tooling (LLM firewalls, guardrail frameworks, agent monitoring) and integrate with SIEM/SOAR.

Skills

Secure coding

OAuth/OIDC/SAML

Prompt engineering

SIEM/CSPM

Data security controls

Python scripting

CI/CD security gates

Vector databases

Adversarial AI testing

LangChain/LangGraph security

Agent kill-switch

Threat modeling

Cloud security (AWS/Azure)

MCP ecosystem

Education

Information security degree or equivalent

Tools

Claude

LangChain

LangGraph

Claude Agent SDK

AWS IAM

Azure Key Vault

Terraform

Job description

DataSpring is seeking a Senior AI Security Engineer to secure AI-driven technology across model configuration, prompt pipelines, and data ingestion. You will design security controls, embed security into build processes, and partner with engineering and data teams. This fully remote, exempt role reports to the Sr.

Director, Security Architecture and Operations. You will lead threat modeling, secure architecture, and guard agency-level security for multi-agent systems, ensuring least-privilege