Senior Forward Deployed Engineer, Cyber
Builds and deploys AI-enabled cybersecurity solutions directly in customer environments: leads technical discovery, architecture, integration, deployment, evaluation, and handover of detection, investigation, and remediation workflows. Requires deep blue-team security expertise, production software engineering, and practical LLM/agentic AI tooling skills.
- Compensation
- Not disclosed
- Location
- United States
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Solutions engineering
- Posted
Skills
Must have
- Deep practical cybersecurity expertise with hands-on blue-team experience in detection, investigation, response, or defensive security engineering
- Strong software engineering skills beyond security scripting: production code, integrations, debugging, testing, maintainable system design
- Record of taking complex technical work from problem definition through deployment, validation, and operational handover
- Practical AI fluency: effective use of AI development tools and judgment about model evaluation, failure modes, and human review
- Experience deploying and troubleshooting software in cloud or customer-hosted environments, with understanding of identity and access, APIs, delivery pipelines, and production observability
- Clear customer-facing communication and translating ambiguous needs into technical requirements and acceptance evidence
- Senior technical judgment: work independently, make tradeoffs explicit, escalate material risks early
- Ownership of useful outcomes including verification, documentation, and adoption after the initial build
Nice to have
- Additional depth in application security, AI agent security, security developer tooling, or purple-team/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
Full description
About Us
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.
Job Summary
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.
Key Responsibilities
1. Turn cyber needs into a technical plan
- 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.
2. Build and integrate AI-enabled security workflows
- 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.
3. Deploy and operate in customer environments
- Own deployment and troubleshooting with the appropriate customer owners, including configuration, access, CI/CD, monitoring, and integration failures.