Senior Forward Deployed Engineer, Cyber

Eliza is a technology services company and Advanced-tier OpenAI partner that's dedicated to helping organizations build and deploy cutting-edge AI solutions. From generative AI and custom LLM integrations to predictive analytics and intelligent automation, we work across industries to bring real-world AI applications to life. Our projects combine deep technical expertise with hands-on client collaboration to solve high-impact problems.

The Senior Forward Deployed Engineer, Cyber builds and deploys AI-enabled security solutions with customers. You will bring deep cybersecurity expertise and strong software engineering skills to work that spans discovery, architecture, integration, deployment, evaluation, and handover. You will own the engineering decisions that turn an ambiguous security problem into a useful, maintainable capability in the customer's environment.

This is a remote role with substantial autonomy and direct client contact. You will work closely with security practitioners, engineering teams, and delivery and commercial partners, making tradeoffs clear and keeping technical commitments credible. Experienced cyber engineers and senior technical leaders who want to remain hands-on are welcome.

Eliza is AI-native. You will use agentic coding tools in your engineering workflow (including OpenAI Daybreak), inspect and verify their output, and make practical decisions about where models help, where they fail, and where human judgment belongs. Client needs and technology change quickly; we value clear thinking, adaptability, and ownership through a validated outcome.

• Lead technical discovery with customer security and engineering teams to understand workflows, systems, data, risks, and operating constraints.

• Define a tractable problem, baseline, architecture, and acceptance criteria; explain what to build, defer, or escalate.

• Align engineering work with measurable security outcomes, such as faster investigation or validated remediation, and make scope, dependencies, and tradeoffs visible.

• Write, review, and debug production software that connects models, APIs, telemetry, and security systems to support detection, investigation, and vulnerability remediation.

• Choose tools and architecture that fit the engagement, balancing speed, reliability, maintainability, and cost.

• Use AI coding tools effectively while retaining ownership of code quality, correctness, and security.

• Own deployment and troubleshooting with the appropriate customer owners, including configuration, access, CI/CD, monitoring, and integration failures.

• Establish clear release, rollback, and operating procedures for the capability you deliver.

• Resolve issues across system boundaries and surface technical or delivery risks early with a recommendation.

• Threat-model AI-enabled workflows and test realistic failure cases, including prompt injection, sensitive-data exposure, and unsafe tool actions, before treating a demonstration as production-ready.

• Build practical controls across prompts, data flows, APIs, and cloud services, including least-privilege access, secrets protection, auditability, and human approval for consequential actions.

• Verify that fixes address the original problem, document limitations, and involve specialist reviewers when needed.

• Explain architecture, evidence, risks, and tradeoffs clearly to technical and nontechnical stakeholders.

• Challenge requests that would undermine security or usefulness and offer practical alternatives.

• Work with delivery and commercial partners on commitments and additional opportunities grounded in demonstrated customer value.

• Produce clear documentation, interfaces, runbooks, and knowledge transfer so customer teams can operate and extend the work.

• Agree operating ownership and handover criteria, or continued operation when the engagement calls for it.

• Turn proven solutions and lessons into reusable engineering patterns, evaluation cases, and playbooks; share technical guidance with colleagues.

• Deep practical cybersecurity expertise, including hands-on blue-team experience in detection, investigation, response, or defensive security engineering, with specific examples of decisions and outcomes you personally owned.

• Strong software engineering skills beyond security scripting: production code, integrations, debugging, testing, and maintainable system design.

• A record of taking complex technical work from problem definition through deployment, validation, and operational handover.

• Practical AI fluency, including effective use of AI development tools and sound judgment about model evaluation, failure modes, and human review.

• Experience deploying and troubleshooting software in cloud or customer-hosted environments, with practical understanding of identity and access, APIs, delivery pipelines, and production observability.

• Clear customer-facing communication and the ability to translate an ambiguous need into technical requirements and acceptance evidence.

• Senior technical judgment: work independently, make tradeoffs explicit, recognize the limits of your expertise, and escalate material risks early.

• Ownership of useful outcomes, including verification, documentation, and adoption after the initial build.

• Additional depth in application security, AI agent security, security developer tooling, or purple-team and red-team work.

• Consulting, professional services, forward-deployed engineering, or comparable direct customer delivery experience.

• Experience with vulnerability remediation, investigation automation, identity and access controls, or secure AI integrations.

• Experience in defense or other demanding security environments, or a record of creating reusable technical capabilities across engagements.