Senior Vellox Product Manager, Cyber Environment Detections
Listed on 2026-08-27
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IT/Tech
Cybersecurity, AI Business & Operations, AI Engineer (Applied/Software)
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Senior Vellox Product Manager, Cyber Environment Detections
The Opportunity:
The P roduct team is defining a new product-led growth business within Booz Allen where you will have the opportunity to design, build, and deliver products to mission and commercial customers at scale . You will experience the energy of a start-up, with the resources, mentorship, and stability of an established tech company – being able to look across industry & capability areas to craft new outcomes leveraging the deep catalog of existing tec hnology and customer solutions.
This team is looking to consistently push the boundaries of what is possible, shaping a future where product investments combined with Booz Allen existing services businesses can supercharge customers .
If you are wanting to build and deliver a product which can outsmart human adversaries while managing massive scales of data – the intersection of where software engineering is meeting digital forensics ;
Booz Allen is seeking a Product Manager to define and build this next generation products . As a Product Manager focus ed on the next generation of detection and remediation engineering, yo u will need to blend your knowledge of how threats manifest themse lves with your passion for eliminating the SIEM & SOAR “noise” and alert fatigue burying analysts today .
This role will be able to leverage the decades of experience which Booz Allen has in delivering differentiated and successful deep security outcomes for customers, but to contribute to shap ing it s fu ture .
One challenge will be to fuse deep domain knowledge around threat modeling & adversarial techniques to develop automated and agentic patterns which unfold the “story” of an attack or vulnerability and the n craft a detection rule to prevent it in the future. This PM willwork acrossthe end-to-end product lifecycle, from identifying high-impact AI use cases, such as like new patterns to detect living-of-the-land (LOTL) attacks, and defining the technical roadmap, to collaborating with engineering and data science teams to build trustworthy, auditable features, and finally, partnering with go-to-market teams to ensure the product successfully meets the complex security and audit requirements of our most regulated customers.
These capabilities will underpin solutions and products across our product portfolio, including Cybersecurity, Defense, Autonomy, AI, Data, and more.
Why environment knowledge matters:
To deliver trustworthy detections and reduce false positives at scale, this role will build capabilities that make customer environmentsfirst ‑classinputs to Ranger systematically capturing asset inventories, topology, control stacks, and telemetry sources. By codifying these signals into environment models and baselines , we’ll tune rule generation to each client’s reality, including cloud, on ‑ prem , and hybrid, improve analyst outcomes, and accelerate time ‑ to ‑ value across regulated and mission contexts.
What You’ll Do :
Own the end‑to‑end vision, strategy, and roadmap for an AI‑driven detection engineering platform that surpasses human‑centric models.
Create a repeatable discovery process to model environments, including assets, topology, identity, and logs, and generate context‑aware, ranked detection rules with KPIs like readiness time, FP reduction, and coverage uplift.
Apply deep knowledge of frameworks like MITRE ATT&CK to design detections aligned to real adversary behaviors across movement, exfiltration, and persistence.
Identify high‑value opportunities for AI automation, enabling autonomous detection creation, triage, and response actions that help users resolve threats, not just notice them.
Design analyst‑focused interfaces that elevate critical threats while suppressing non‑actionable SIEM/SOAR‑style noise.
Build DaC workflows using Git‑based version control, CI/CD testing, and automated deployment across massive, normalized event pipelines.
Integra…
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