Staff Software Engineer, AI/ML, Google Cloud Security at Google
Reston, VA
$207,000–$301,000from the description
Jul 13, 2026
Reston, VA
Jul 21, 2026
What this job asks for AI summary
A staff-level engineering role on Google Cloud Security's Defense and Consulting team, focused on building and leading AI/ML systems for security operations — including model deployment, optimization, and data processing pipelines. The position carries significant technical leadership responsibility: setting direction for cross-functional teams, shaping a long-term product and technology roadmap, and driving the integration of generative and agentic AI into security workflows. Suited to a seasoned ML engineer with a background in large-scale distributed systems and an interest in the cybersecurity domain.
Staff level · 8+ years · Washington-Arlington-Alexandria, DC-VA-MD-WV · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 340 people in the Washington-Arlington-Alexandria, DC-VA-MD-WV area plausibly meet what this posting asks for (software developers). range 140–500
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $158,337 (middle half $126,441–$180,105). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The role has two listed work locations (Reston, VA and New York, NY); Reston, VA was used as the primary CBSA since it is listed first. The New York CBSA (35620) is equally valid.
The degree requirement states 'Bachelor's degree or equivalent practical experience,' so no formal degree is hard-gated and the degree requirement is set to None.
The compensation range of $207,000–$301,000/year is stated explicitly, plus a 20% bonus target and equity — the bonus and equity are noted here as they cannot be captured in the comp fields.
ML infrastructure experience (model deployment, model evaluation, data processing, debugging, fine-tuning) is listed as a single 5-year requirement in the minimum qualifications; the sub-components are extracted as individual skills to surface the concrete technologies/activities involved.
Generative AI integration and LLM interfaces are listed under minimum qualifications with firm language ('Experience integrating generative AI tools or LLM interfaces into workflows'), making them hard gates. Agentic AI and deeper LLM experience appear again under preferred qualifications and are marked preferred there.
GCP is listed under preferred qualifications ('major cloud platforms, e.g., GCP') alongside distributed systems and security domain experience — all marked preferred.
The role carries genuine Staff-level signals: cross-functional technical leadership, setting technology roadmap, influencing a distributed team, and org-wide AI velocity — consistent with the explicit 'Staff' title.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): software development, technical leadership.
Read the full posting
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