
Infrastructure Engineer Lead
New York City, NYFull-timePosted 1mo agoStill listed 5 days ago
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Job overview
AEGIS is building AI-driven cybersecurity systems to detect and stop adversarial AI attacks. The Infrastructure Engineer Lead will architect and scale data-ingestion and AI infrastructure, including pipelines, GPU workload orchestration, and real-time feedback loops for distributed AI agents. The team emphasizes adaptability, speed, and execution in a fast-changing environment. Security and detection systems experience is a bonus.
Skills & qualifications
Skills
Qualifications
Full job description
We’re a team of ex-Google engineers who built some of the largest defensive platforms on the planet — Safe Browsing and reCAPTCHA. Now, we’re striking out on our own to tackle an even bigger challenge: stopping the new wave of adversarial AI attacks already hitting organizations today.
We're going after a $5B+ market, ripe for disruption. Traditional detection methods are too slow to keep up. Adversaries are using AI to craft customized, high-evasion attacks — and old-school rules-based systems don’t stand a chance.
Your Mission: Architect the foundation for a constellation of AI Agents — fast, cheap, and high-precision — that work together to detect and stop emerging threats. AI is only as good as the data it learns from and in this role, you’ll be the architect responsible for making sure our system has the very best. You’ll build and scale the infrastructure that ingests rich data streams from partners, continuously scans the internet for new threats, and monitors billions of customer events in real time to extract high-signal behavioral patterns. This is detection at internet scale, and it requires a mindset that thrives at the intersection of performance, precision, and adaptability. Beyond data ingestion, you’ll also design and operate the AI infrastructure that powers a distributed network of intelligent agents. That means everything from building pipelines to fine-tune models with fresh threat data, to orchestrating GPU workloads across dynamic clusters, to implementing real-time feedback loops that learn from the wild and continuously evolve. This isn’t just ML ops- it’s the foundational system that lets AI fight adversarial AI, and you’ll be building it from the ground up.
Why This Is Hard (a.k.a. Why It’s Fun)
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The models change daily. Literally. What worked yesterday might be obsolete tomorrow.
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The adversaries are smart — and getting smarter. We’re in a real-time arms race against AI-enabled attackers crafting tailored, evasive payloads.
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There’s no playbook. We’re building new detection paradigms as fast as the threats evolve. It’s high-stakes, high-impact work — and you’ll be in the arena from day one.
If you’re the kind of engineer who lives for tough problems and fast feedback loops, this is your kind of challenge.
Why We’ll Win
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The market is massive — $7B+ and growing fast — and incumbents are too slow to adapt.
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We’ve done this before. Our team built the core technology behind Safe Browsing (5B+ users) and reCAPTCHA (protecting 5M+ websites) while at Google.
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This is our third time building a category-defining security business. We know how to scale both the tech and the company.
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AI and security are in our DNA. We don’t bolt it on — we build it in from day one.
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We only hire top performers. Most of our team were top 1% engineers at Google — if you were the best at your last job, you’ll feel right at home here.
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We move fast. No politics. No hierarchy. Just brilliant people solving hard problems, together.
What We’re Looking For: We want engineers who are outgrowing their current roles — people who want to build at the very edge of AI and cybersecurity.
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You thrive in relentless environments where learning curves are steep and every day is a new challenge.
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You care about speed, execution, and complete thinking more than resumes or titles.
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You think in weeks and days, not months and quarters.
Despite 30+ years of combined AI experience on the founding team, we know today’s landscape changes too fast to rest on credentials. We prioritize adaptability and speed of learning above all else. Our culture:
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Flat, flexible, and fast.
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You’ll own your decisions and your tech stack.
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You’ll have clear KPIs for success — but how you get there is up to you.
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Development cycles are measured in days, not weeks.
If you’re hungry to build AI that fights AI, and want to work with a team that moves at the speed of the real world, come talk to us. Requirements: 10+ years of experience Experience scaling AI infrastructure or MLOps Experience building in a fast paced environments Bonus: Experience security/detection systems Experience working in adversarial environments (T&S, security, fraud)
How this job compares
Set against the 5,088 open Infrastructure Engineer jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This postingNot listed
- New York median$160–235K/yr239 salary ranges
- US median$50–63/hr104 hourly ranges
- Openings
- Olive Jobs lists 296 open Infrastructure Engineer jobs in New York and 5,088 across the US. 10% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 10 years of experience — more than three in four Infrastructure Engineer postings that state a minimum ask for (median 6 years, across 3,962 postings).
- Education
- 740 of the 5,088 open Infrastructure Engineer jobs (15%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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