Sr. Cyber Security Engineer - Automation

Role

The Senior Automation Security Engineer designs, builds, and operates scalable automation to strengthen the organization’s security posture while enabling engineering velocity. The role focuses on reusable Python services, secure CI/CD patterns, Terraform-based guardrails, AWS security automation, and governed internal AI/agent workflows.

Key Responsibilities

Automation Platform Engineering

• Design, build, and operate reusable Python services, libraries, CLIs, and integrations that automate security controls and operational workflows.
• Define standards for reliability, testing, observability, secrets handling, access control, and lifecycle ownership of automations.
• Automate workflows including identity and access reviews, cloud configuration remediation, evidence collection, findings enrichment, exception management, and incident response orchestration.

GitHub, GitHub Actions & DevSecOps

• Own and improve GitHub Actions patterns for secure CI/CD, including reusable workflows, OIDC-based cloud access, artifact controls, approvals, and policy checks.
• Integrate code scanning, dependency controls, secrets detection, IaC scanning, tests, and release gates into engineering workflows.
• Review workflow and repository permissions, third-party actions, supply-chain risks, and runner security and drive remediation.

Terraform & AWS Security Automation

• Design and maintain Terraform modules, guardrails, and policy-as-code controls for AWS environments.
• Automate secure AWS configuration across IAM, Organizations, VPC, CloudTrail, CloudWatch, S3, KMS, Lambda, ECS/EKS, Secrets Manager, and related services.
• Build detection and remediation flows with least-privilege, change controls, dry runs, rollbacks, and audit-ready logging.

Internal AI Enablement & Agent Development

• Develop governed internal AI automations and agents using approved models, tools, knowledge sources, and identity boundaries.
• Design agent workflows with explicit tool scopes, input validation, prompt-injection defenses, audit logs, evaluation cases, and human-in-the-loop approvals for material actions.
• Create reusable patterns for tool calling, retrieval/RAG, workflow orchestration, context handling, and secure deployment.
• Champion responsible AI-assisted or “vibe coding” practices, including review accountability and protection of internal data.

Technical Leadership

• Translate security and operational needs into an automation roadmap, architecture, and measurable outcomes.
• Lead technical design reviews, mentor engineers, and partner with platform, cloud, SOC, and application teams.
• Communicate tradeoffs and risk clearly to technical and non-technical stakeholders.

Qualifications

Required

• Strong Python software engineering skills, including API integration, testing, packaging, error handling, and production troubleshooting.
• Hands-on expertise with GitHub and GitHub Actions (reusable workflows, OIDC, permissions, secrets, CI/CD controls).
• Strong Terraform experience: modules, state, plans, testing, and policy/guardrail implementation.
• Deep practical understanding of AWS security and cloud architecture, especially IAM, network boundaries, logging, encryption, and serverless/container services.
• Experience designing reliable, observable, least-privileged automation safe for rollout.
• Demonstrated ability to lead design discussions, review code, and guide cross-team work.
• Working knowledge of AI/LLM application risks and engineering controls for safe agentic automation.

Preferred

• Experience with security orchestration, SIEM/SOAR, detection engineering, incident response, or vulnerability-management automation.
• Experience with policy-as-code and cloud security tools such as OPA, Checkov, tfsec, Trivy, AWS Config, Security Hub, or GuardDuty.
• Hands-on delivery with LLM APIs, agent frameworks, MCP, RAG, evaluation frameworks, or enterprise AI platforms.
• Relevant certifications (AWS Security Specialty, AWS DevOps Engineer, CISSP, Security+, or comparable).
• Experience operating workloads with Docker, Kubernetes, ECS, or EKS.

How Success Is Measured

• Automation reduces manual work, improves control coverage, and has clear owners, runbooks, telemetry, and SLAs.
• GitHub Actions and Terraform controls improve delivery security while remaining usable for engineering teams.
• AWS risks are prevented, detected, or remediated through durable automation with measurable recurrence reduction.
• Internal AI agents deliver bounded business value while passing security review and operational-readiness criteria.
• Teams adopt consistent, safe AI-assisted development practices and reusable automation patterns.

Level Expectations

• Independently own ambiguous, cross-team automation problems from design through production operation.
• Set technical direction and guardrails; mentor others and raise engineering quality, security posture, and AI readiness.

Hiring Process Note

• External candidates may be required to attend an in-person interview at one of the company’s locations prior to a hiring decision. Reasonable accommodations for applicants with disabilities are available on request.