About the Team
Security Automation & Integration Engineering (SecAIE) transforms cybersecurity operations by architecting intelligent automation that turns manual processes into scalable, decision-accelerating systems. We're the engineering excellence partner within Cybersecurity and Trust - building the unified data foundation, intelligent automation, and decision support tools that enable security teams to make precise, data-driven decisions at machine speed.

We partner closely with Security Leadership, Operational Teams, Engineering Teams, and Governance/Risk Teams to deliver platforms that multiply their effectiveness. Our current charter contributes directly to Workday's Active Defense pivot - building the reliable data and platform substrate that lets security teams execute at machine speed and out-adapt AI-driven threats.

We're a small, high-impact team that values curiosity, pragmatism, and collaboration. We believe working solutions beat perfect designs, unified context beats massive datasets, and partner success is our success. Leveraging AI to augment how we do security engineering is an active opportunity for the team, and one we expect this role to help lean into.

About the Role

We're looking for a Cybersecurity Engineer to join SecAIE and take primary ownership of the infrastructure, automation, and platform reliability that Workday's Active Defense charter runs on. You'll spend most of your time engineering the substrate - the reliable data pipelines, cloud infrastructure, CI/CD, and cross-tool integrations - that turns security data into a dependable foundation for AI-driven execution and decision-making. This role is ideal for someone who loves turning messy operational problems into clean, self-serve infrastructure, who can walk into an ambiguous ask and come back with a proposal, and who treats AI tooling as a force multiplier rather than a novelty.

You will bring working knowledge of cybersecurity concepts and best practices from day one - enough to reason about identity and access, secrets and key management, secure-by-default cloud configuration, and the shape of common security data (vulnerabilities, incidents, identity, threat intel). You will not be expected to be the deepest security specialist in the room; you will partner with domain experts across our security organization and build the plumbing that makes their work faster, more reliable, and more measurable.

Responsibilities:

• Own the infrastructure-as-code and platform substrate that our security data and automation services run on - from tuning existing services to landing net-new modules and multi-environment rollouts
• Design, build, and operate the automations and data pipelines that ingest, transform, and route security data reliably at scale
• Extend and harden our continuous delivery and cloud-security posture so every service is deployable, observable, and secure by default
• Take partner requests from vague to shipped: scope the problem, propose approaches, choose one, and drive it through design, review, rollout, and operational readiness
• Build and maintain integrations across security tools and enterprise platforms - SOAR, SIEM, EDR, vulnerability scanners, ticketing - to accelerate response and reduce toil
• Raise the team's AI-augmented engineering floor: shared skills, reusable scaffolds, and a review discipline for AI-generated code
• Iterate quickly: prototype, test, ship, learn, improve - and bring the team with you

About You

You're a curious engineer who owns problems rather than tickets. You're drawn to ambiguous, messy asks and you enjoy learning a domain deeply enough to propose the right solution, not just implement one that was handed to you. You bring high agency: you can move a partner's rough problem statement to a shipped, operational answer without waiting to be told each next step. You're comfortable turning a partner's Slack thread into a written proposal, and comfortable when the answer to "whose ticket is this?" is "nobody's yet - I'll draft one." You know when to escalate and when to just close the loop yourself. You default to automation over toil, shared components over copy-paste, and reliable defaults over one-off heroics. You use AI tooling deliberately and can articulate where it accelerates you and where it does not. You communicate clearly, ask good questions, and genuinely enjoy collaborating across teams to solve hard problems.

Basic Qualifications:

• Strong Python skills with hands-on automation and integration experience (APIs, Lambdas, batch jobs, workflow glue), including code review, testing, and shipping to production

• Deep hands-on experience with infrastructure-as-code (Terraform) and CI/CD (Jenkins, GitHub Actions, or similar), including production ownership

• Working fluency across a broad AWS surface (Lambda, ECS, S3, IAM, KMS, VPC, and at least one compute service such as EMR, Batch, Glue, or EKS)

• Experience with containerization (Docker) and modern deployment patterns

• Working knowledge of core cybersecurity practices - identity and access, secrets and key management, secure-by-default cloud configuration, and reasoning over common security data (vulnerabilities, incidents, identity, threat intel) - so you can build for security outcomes, not just infrastructure ones

• Comfortable owning on-call and operational readiness (runbooks, alarms, SLOs) for services you deliver

Other Qualifications:

• Security domain depth - hands-on with security tools or data for triage and investigation (SIEM, vulnerability scanners, identity systems, cloud security posture, secrets management); working knowledge of vulnerability data and workflows (scoring, prioritization, at least one scanner in practice); familiarity with security orchestration platforms as an integration target; curiosity about deception and adversary-emulation tooling

• DevOps / platform depth - contributing to shared platform components (reusable Terraform modules, internal libraries, developer tooling); observability tooling (metrics, logs, traces) for services you own; building Slack bots, workflow automations, or enterprise tool integrations (Jira, PagerDuty, ServiceNow, etc.)

• Data engineering depth - distributed data technologies (Spark, Trino, Hive, S3-as-datalake) and SQL; comfort reasoning about shared schemas or data contracts that span team boundaries, treating what / who / state as a first-class artifact rather than fields on a table

• AI-augmented engineering depth - hands-on use of AI-augmented development workflows (Copilot, coding agents, LLM-driven code review, agentic pipelines) with a point of view on where they help; experience contributing to LLM-based systems moving toward production (agent frameworks, tracing and observability for agent runs, offline evaluation of prompts and tool calls)

• Comfort operating in ambiguous problem spaces where you help define the solution, not just implement it

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: USA.VA.Reston

Primary Location Base Pay Range: $130,200 USD - $195,400 USD

Additional US Location(s) Base Pay Range: $117,800 USD - $210,000 USD

Additional Considerations:

If performed in Colorado, the pay range for this job is $124,000 - $186,000 USD based on min and max pay range for that role if performed in CO.

The application deadline for this role is the same as the posting end date stated as below:

08/14/2026

Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

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