Senior Technical Consultant - Forward Deployed AI Security Engineer

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.

At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.

We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.

We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.

Perform AI runtime assessments. Inventory AI applications, models, agents, copilots, MCP servers, plugins, and data flows. Evaluate prompt/response paths, tool-calling behavior, identity chains, and attack surface. Produce scored findings covering prompt injection, jailbreaks, data leakage, model and agent misuse, shadow AI, and unsafe autonomous actions. Deploy and operationalize AI security tools. Stand up, integrate, and harden Palo Alto Prisma AIRS (runtime firewall, API intercept, model security, agent security, red teaming, posture), Koi Agentic Endpoint Security, Onyx Secure AI Control Plane / Guardian Agent, Zenity (observability, AISPM, exposure management, runtime boundaries), Zscaler AI Security (AI Guard, asset management, zero-trust access to GenAI), and CrowdStrike Falcon AIDR and related Falcon modules. Design the control plane. Map traffic through AI gateways, inline intercepts, endpoint agents, SaaS connectors, and identity providers. Define allow/block/human-in-the-loop policies for prompts, tool use, MCP calls, package and extension installs, and agent actions. Integrate with the existing stack. Wire AI security telemetry into SIEM/SOAR, EDR/XDR, SSE/Zero Trust, IAM, CSPM, and ticketing. Correlate AI events with endpoint, identity, and network signals so detections are actionable, not noisy. Red team and validate. Run adversarial testing against LLMs, agents, and copilots. Convert findings into enforceable guardrails. Re-test after deployment and prove residual risk is accepted or closed. Own customer outcomes. Embed with the account. Drive architecture workshops, implementation sprints, policy workshops, and knowledge transfer. Leave behind runbooks, detection content, and an operating model the customer can run without you. Communicate with precision. Write assessment reports, risk memos, architecture decision records, and board-ready summaries. Brief CISOs, AI platform owners, legal/privacy, and engineers in clear, idiomatic English. Escalate risk without inflating it. Feed product and practice. Return field patterns, integration gaps, and detection ideas to product, threat research, and delivery teams. Help standardize playbooks for repeatable AI security deployments.

Exceptional written and spoken English. You can write a 20-page technical assessment, a one-page CISO brief, and a customer email with equal clarity. Grammar, tone, structure, and technical precision are non-negotiable. Candidates will be evaluated on writing samples and live briefing quality. Hands-on deployment experience with multiple of the following platforms in production or customer environments: Palo Alto Prisma AIRS , Koi Agentic Endpoint Security , Onyx Security , Zenity , Zscaler AI Security , and CrowdStrike (Falcon AIDR, Falcon XDR/NG-SIEM, or adjacent Falcon modules used to secure AI runtime). Demonstrated ability to perform AI runtime assessments : discovering AI assets, inspecting prompt and tool-call traffic, identifying prompt injection / jailbreak / data-exfiltration / agent-abuse paths, and translating findings into controls. 5+ years in cybersecurity engineering, security architecture, or technical consulting, with at least 2 years focused on cloud, application, or AI/LLM security. Working fluency with modern AI architecture: LLMs and SLMs, RAG, agents and multi-agent systems, MCP servers and tools, copilots (e.g., Microsoft 365 Copilot, GitHub Copilot, Cursor, Claude Code), model gateways, and common cloud AI platforms (AWS Bedrock, Azure AI Foundry / OpenAI, Google Vertex AI). Strong integration skills across identity (Okta, Entra ID), endpoints, network/SSE, APIs, Kubernetes or container platforms, and logging pipelines. Ability to operate independently on-site: debug failed connectors, certificates, proxies, agents, and policy conflicts without waiting for a back-office engineer. Willingness to travel extensively and embed with customers for multi-day or multi-week deployments. Bachelor’s degree in Computer Science, Cybersecurity, Engineering, or equivalent practical experience.

Prior forward-deployed, professional-services, or resident-engineer experience (Palantir-style FDE, vendor PS, or Big Four cyber delivery). Vendor certifications or deep product credentials in Palo Alto Networks, Zscaler, CrowdStrike, or adjacent SSE/XDR platforms. Experience with AI red teaming methodologies, OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic Applications, MITRE ATLAS, and NIST AI RMF. Scripting and automation in Python and one of Bash, PowerShell, or Go. Comfort reading application and infrastructure-as-code. Familiarity with DLP, DSPM, secrets detection, model scanning, and software supply-chain controls as they apply to AI artifacts (models, packages, extensions, MCP servers). Experience in regulated industries (financial services, healthcare, government) where AI use must be auditable. Public speaking, workshop facilitation, or published technical writing on AI security.

Palo Alto Prisma AIRS: AI runtime security (network and API intercept), model security, agent security, AI red teaming, posture management, and AI gateway controls. Koi Agentic Endpoint Security: Discovery and risk scoring of endpoint-resident AI software, packages, extensions, local models, agents, and MCP servers; install governance and session-aware AIDR. Onyx: Secure AI control plane — continuous AI asset discovery, session capture, identity-aware attribution, and Guardian Agent enforcement (allow, redirect, require approval, or block). Zenity: AI agent observability, AI security posture management (AISPM), exposure management, runtime boundaries, and coverage across SaaS copilots, custom agents, and coding agents. Zscaler: Zero Trust access to GenAI, AI asset management, AI Guard runtime inspection of prompts and responses, and correlation of AI-event telemetry with the Zero Trust Exchange. CrowdStrike: Falcon AIDR for runtime detection and response across endpoint, SaaS, and cloud AI use; integration with Falcon XDR / Next-Gen SIEM for investigation and automated response.

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