Security Ai Engineering

Security Ai Engineering Jobs

3 jobs found

Today

Cybersecurity Engineer/AI

Systems Planning and Analysis Offutt AFB, NE

Offutt AFB, NE

Today

Full time Ai Security Cyber Security Engineer Cybersecurity Architecture

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Job Description

Systems Planning and Analysis (SPA) is hiring an Enterprise Cybersecurity and AI Systems Architect at HQ USSTRATCOM (Offutt AFB, NE) to support NC3 enterprise modernization, futures capability development, and RDT&E. This onsite role combines cybersecurity engineering, system architecture, and AI-related defensive security evaluation to improve risk reduction and operational resilience across the NC3 enterprise.

Responsibilities

Provide cybersecurity engineering and architecture support for nuclear command, control, and communications (NC3) enterprise modernization, futures capability development, and RDT&E activities.
Coordinate with external NC3 enterprise stakeholders and support synchronization and alignment of enterprise integration work to ensure consistency and compliance with executive leadership direction.
Apply expertise in Frontier AI and Agentic AI workflow models and evaluate Artificial (Superior) Intelligence capabilities for defensive cyberspace security use cases, including engineering, architecture design, and procedural considerations for defense against adversary use of frontier AI.
Advise on NC3 enterprise cryptography, cyber pilots and prototypes, future cyber capabilities, and overall architecture design.
Evaluate and recommend cyberspace policy changes needed to enable accelerated transition to a modernized cyber secure NC3 enterprise architecture.
Prepare, present, and translate complex cyber concepts for senior-level engagements, including support as directed for the NEC Director and NC3 Enterprise Lead for Congressional, National, DoW, OSW, JCS, and Service level meetings.
Lead cross-functional teams to drive NC3 enterprise cyberspace modernization, incorporating USCYBERCOM, NSA, Services, and other departments and agencies as required.
Perform architecture and system design work across cyberspace and AI activities spanning assessment, development, integration, and management, addressing risk reduction and operational resilience across personnel, hardware, software, support facilities, and associated equipment.

Requirements

U.S. citizenship and an active Top Secret (TS) security clearance with SCI eligibility, plus day-one eligibility for NC2-ESI, NATO, and SAR, with the ability to maintain all required clearances and program eligibilities throughout employment.
Bachelor’s degree in Computer Science/Engineering, Information Technology, Cybersecurity, or a related field (or Master’s Certificate in Artificial Intelligence, Machine Learning, Computer Science/Engineering, Information Technology, Cybersecurity, or related field).
At least 10 years of combined experience in cybersecurity engineering, artificial intelligence, and information systems and network security for DoW information technology programs.
Background, knowledge, and experience in NC2/NC3 operations and capabilities, strategic nuclear operations, joint integrated operations, joint warfighting doctrine, unified CCMD structures, and global command and control constructs.
Ability to work full-time, 5 days per week onsite at USSTRATCOM HQ and the iREACH/REACH facility.
Certifications: one or more of Cisco CCNA, CompTIA Security+, CompTIA SecurityX, CCSP, or FITSP-O.

Desired Qualifications

Master’s degree in Computer Science/Engineering, Cybersecurity, Artificial Intelligence, or a related field.
Knowledge and experience in critical command and control requirements, including NC2 and NC3 operational capabilities and procedures.
Knowledge of national, DoD, and CJCS guidance, including CJCS Emergency Action Procedures, USSTRATCOM Emergency Action Procedures, CJCS Instructions, and Presidential Policy Directives.
Experience supporting the USSTRATCOM Global Operations Center (GOC) and/or other operations centers at Combatant Commands, Joint Staff, or DoD levels.

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2d ago

Cybersecurity AI Forward Deployed Engineer

Accenture Kirkland, WA

Kirkland, WA

2d ago

$59k - $235k/yr Full time Adversarial Ai Security Agentic Ai Security Ai Security

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Job Description

Accenture Security is hiring a Cybersecurity AI Forward Deployed Engineer to embed inside client enterprises and help make agentic AI systems secure, governed, and resilient in production. This onsite role in Kirkland, WA combines hands-on security engineering with AI security architecture, supporting production deployments across complex environments and multi-stakeholder programs.

What you’ll do

Own AI security design from assessment through hardened deployment for production agentic deployments, including LLM systems, multi-agent pipelines, RAG architectures, and MLOps infrastructure
Perform hands-on security engineering using agentic coding tools to build AI-powered detection, automated threat response tooling, security assessment frameworks, and governance automation with Claude Code, Cursor, or GitHub Copilot
Manage AI threat surfaces at program scale using OWASP LLM Top 10 controls, prompt injection hardening, model extraction prevention, adversarial input defenses, and AI supply chain security across concurrent client workstreams
Architect and govern AI security controls across the enterprise stack, covering identity and access for AI systems, data pipeline security, model serving security, and integration risk across AWS, Azure, or GCP
Support implementation of AI governance frameworks applied to live systems, including EU AI Act and NIST AI RMF, plus model risk management for production use
Help shape AI reinvention security strategy for client CISO and CTO by developing risk-adjusted investment cases, security architecture roadmaps, and AI governance operating models aligned to commercial outcomes
Define and share reusable security patterns, playbooks, and accelerators to scale the Secure AI practice across multiple engagements
Contribute to and support architecture design sessions, threat modeling workshops, and code-with sessions with client engineering and security leadership

Key requirements

3+ years of engineering experience in production environments with cybersecurity depth in at least one area: AppSec, SecOps / detection engineering, cloud security, IAM, offensive security / penetration testing, or GRC
1+ year of hands-on experience designing and deploying agentic AI solutions in production (the experience is required, not theoretical familiarity)
3+ years working with cloud platform security fundamentals on at least one provider (AWS, Azure, or GCP): IAM, network security, secrets management, and AI service security configurations
Bachelor’s degree or equivalent (minimum 12 years work experience). If Associate’s degree, minimum 6 years work experience required
Proven ability to communicate security risk in business terms, including translating threat exposure into risk-adjusted investment rationale for a CISO or CFO

Technologies you’ll work with

Claude Code, Cursor, GitHub Copilot
OWASP LLM Top 10, EU AI Act, NIST AI RMF
AWS, Azure, GCP
LLM systems, multi-agent pipelines, RAG architectures, MLOps infrastructure

Compensation and schedule

Salary: USD 59,100 - 235,100 per year. This role is onsite in Kirkland, WA.

Travel may be required: 0 to 100% depending on business need and client requirements.

Benefits

Medical, dental, vision, life, and long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

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4d ago

Sr AI Engineer, Security

News Corp Austin, TX

Austin, TX

4d ago

Full time Backend Developer Ai Agent Security Ai Guardrails

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Job Description

Build and lead AI security for agent and model platforms across AWS and GCP, focused on practical controls, guardrails, and incident readiness.

Responsibilities

Secure the AI platform across AWS and GCP.
Design, enforce, and operationalize guardrails for AI workloads on:
- AWS using Bedrock, Lambda, IAM, KMS, SCPs, GuardDuty, and Security Hub.
- GCP using Vertex AI, IAM, VPC Service Controls, Org Policies, Security Command Center, and Cloud KMS.
Define how agents and non-human accounts are identified and authorized using:
- Short-lived, narrowly scoped credentials
- Delegated user permissions
- A per-agent audit trail to limit blast radius for misbehavior
Build agent containment including separate read and write permissions, network egress controls, sandboxed execution, approval gates for high-risk actions, and kill switches.
Design an agent gateway or control plane to keep agents and tool calls within approved limits.
Secure the AI supply chain by governing model and dataset intake, including scanning for unsafe formats such as pickle; vetting model and dataset sources from public hubs such as Hugging Face; approving new MCP servers and agent tools; and maintaining an AI-BOM inventory of models, data, and tools used by each system.
Defend against prompt injection, tool poisoning, RAG poisoning, and sensitive data leakage.
Implement detection and logging for agent and model activity; own AI-specific incident response playbooks.
Lead threat modeling for new products, features, and internal solutions spanning consumer experiences to internal tools and agent workflows, using frameworks such as STRIDE, OWASP LLM/GenAI Top 10, MITRE ATLAS, and OWASP ASVS; translate outcomes into design requirements and release criteria.
Review pull requests, architecture designs, and release readiness for apps to agent fleets, providing concrete suggestions that move work forward.
Create paved-road frameworks, reference architectures, and secure-by-default templates that prevent classes of risk rather than handling issues one PR at a time.
Embed security into CI/CD with secrets scanning, SAST/SCA, GitHub Actions hardening, and policy-as-code in Terraform.
Run an ongoing red-team and evaluation program for models, agents, and LLM apps; test AI features before launch.
Partner with the global cybersecurity team to align Realtor.com AI and cloud security with group standards, policies, and risk frameworks.
Coordinate across News Corp businesses on incident response, threat intelligence, and vulnerability disclosure.
Share AI security patterns, threat models, and lessons learned with other News Corp businesses and bring insights back to Realtor.com.
Build agents to support security work, including triage, alert investigation, IAM least-privilege audits, and creating tested, secure-by-default fix PRs.
Use Claude Code, Devin, and MCP to accelerate the security team and share reusable patterns with other engineering teams.
Track emerging AI threats, incidents, research, and vendor capabilities, converting them into platform actions.
In major industry incidents, assess exposure quickly and lead response coordination.
Prototype new controls when best practices do not yet fit, run small experiments, measure results, and roll improvements into platform standards.
Write internal briefings on major developments and recommend when to adopt, pilot, or skip tools and practices.
Create and run AI security training for engineers, product teams, and the wider company covering prompt injection, data leakage, excessive agency, and secure use of tools like Claude, Glean, Devin, and Gemini.
Act as the AI security voice in platform strategy: evaluate vendors and models, set expectations for production readiness, and shape AI governance across the AI lifecycle.
Brief leadership on AI risk and where to invest.
Represent Realtor.com externally via conference talks, open-source work, or industry working groups.

Requirements

5+ years in cybersecurity, cloud security, AppSec/product security, or security platform engineering.
Hands-on depth in AWS security plus real experience in GCP (or strong multi-cloud experience).
Security thinking grounded in permissions, scopes, logs, approval gates, data boundaries, and rollback rather than relying on “do not do X” prompts.
Experience securing LLM or agentic systems, including prompt injection defenses, retrieval and data-boundary risks, agent identity, and model or tool supply-chain integrity.
Threat modeling experience for products and platforms (not only infrastructure), including leading sessions with engineers and product managers and turning output into requirements they follow.
Hands-on experience building with agents, tool calling, or MCP, and with AI coding tools.
Strong code-review skills in at least one of Python, TypeScript, or Go, and comfort with Terraform/IaC.
Experience with zero trust, least privilege, SSO/OIDC/OAuth, secrets management, and vulnerability management.
Experience working within a larger security organization (parent company, central security team, or federated model) with the ability to balance local execution speed with enterprise alignment.
Stay current on AI security research, incident write-ups, and community learning; apply something recent.
Builder mindset: prototype new controls and operate where playbooks are still forming.
Ability to explain risk to any audience, from PR comments to executive briefings to company-wide training.

Technologies

AWS, GCP
Bedrock, Lambda, IAM, KMS, SCPs, GuardDuty, Security Hub
Vertex AI, VPC Service Controls, Org Policies, Security Command Center, Cloud KMS
Hugging Face, MCP
Claude Code, Devin, Claude, Glean, Gemini
Python, TypeScript, Go
Terraform
CI/CD, GitHub Actions, SAST, SCA
STRIDE, OWASP LLM/GenAI Top 10, MITRE ATLAS, OWASP ASVS, RAG, pickles

Benefits

Inclusive and competitive medical, Rx, dental, and vision coverage
Family forming benefits
13 paid holidays
Flexible time off
8 hours of paid volunteer time off
Immediate eligibility into Company 401(k) plan with 3.5% company match
Tuition reimbursement program for degreed and non-degreed programs
1:1 personalized financial planning sessions
Student debt retirement savings match program
Free snacks and refreshments in each office location

Nice to Have

AWS Security Specialty, Google Professional Cloud Security Engineer, CCSP, CISSP, OSCP, or GIAC (GCSA/GWEB)
Experience red-teaming or evaluating AI models or agents
Familiarity with NIST AI RMF, ISO 42001, Google SAIF, CoSAI, NIST SSDF, or the EU AI Act
Experience securing Snowflake (RBAC, masking, network policy)
Conference talks, published research, or open-source security contributions

Work Location and Work Style

Onsite in Austin, TX, United States
In-person collaboration is emphasized; for most roles, employees work four or more days in the office

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