চাকৰি
পাৰ্টনাৰ ফিডৰ পৰা
Detection Engineer
অনুৰোধ কৰিলে মূল্য
বিৱৰণ
- নিয়োগৰ প্ৰকাৰ
- ফুল-টাইম
- ৰিম'ট
- হয়
- কোম্পানী
- Artemis
বিৱৰণ
About the Role
We're looking for a Detection Engineer to own the detection content that powers the Artemis platform. You'll design, build, test, and continuously tune high-fidelity detections across cloud, identity, endpoint, and SaaS environments — treating detection as code, and using AI as a force multiplier at every step: authoring rules with AI assistance, and building anomaly detections that learn what's normal in each environment and flag what isn't. Detections at Artemis don't just fire alerts; they feed an AI-native investigation pipeline, so precision, rich context, and machine-readable output matter as much as coverage. This is a hands-on engineering role where every rule you ship directly determines what threats we catch for customers and how fast we catch them.
Responsibilities
• Build and maintain the detection library - Design, implement, and own high-fidelity detections across cloud (AWS, Azure, GCP), identity (Okta, Entra ID), endpoint (EDR), and SaaS log sources, from hypothesis to production.
• Practice detection-as-code - Manage detection content like software: version-controlled rules, peer review, automated validation and testing, and CI/CD deployment across customer environments.
• Map and close coverage gaps - Measure detection coverage against MITRE ATT&CK, prioritize gaps based on real-world threat activity, and systematically close them.
• Validate against real attacks - Build and run attack simulations and test harnesses to prove detections fire on true positives and stay quiet on benign activity, before and after they ship.
• Tune relentlessly - Own false-positive and false-negative rates across the fleet: analyze detection performance data, tune noisy logic at the source, and sunset detections that no longer earn their keep.
• Use AI to write detections at scale - Leverage AI throughout the detection lifecycle: use AI-assisted workflows to author, convert, test, and document rules faster than any traditional team could, and build the tooling that makes AI-generated detection content trustworthy enough to ship.
• Build behavioral and anomaly-based detections - Go beyond static signatures: establish behavioral baselines of normal activity per environment (identity, cloud, SaaS usage patterns) and engineer anomaly detections that surface deviations — impossible travel, unusual privilege use, novel API activity — with high signal and low noise.
• Engineer detections for AI-powered investigation - Design detections that produce rich, structured context so the Artemis platform can investigate and resolve cases autonomously.
• Turn intelligence into detections - Translate threat intelligence, incident findings, and threat hunt results from our research and SOC teams into durable, behavioral detection logic.
• Partner with the SOC and research teams - Close the loop with Apollo analysts and security researchers: use case outcomes and analyst feedback to drive detection improvements, and give them documentation that makes every alert investigable.
• Support customer-specific tuning - Adapt and tune detection content to each customer's environment and business context, reducing noise without sacrificing coverage.
Qualifications
• 5+ years of hands-on cybersecurity experience, with significant time in detection engineering
• Proven track record designing, building, and tuning detections at scale across SIEM, EDR, or custom detection platforms
• Strong proficiency in detection languages and formats such as Sigma, KQL, SPL, or YARA-L, and comfort writing code (Python preferred) for automation and testing
• Deep knowledge of attacker tactics, techniques, and procedures (MITRE ATT&CK) and how they manifest in logs across cloud, identity, endpoint, and SaaS telemetry
• Experience with detection-as-code workflows: Git, peer review, automated testing, and CI/CD for detection content
• Experience using AI tools to accelerate detection authoring, tuning, or validation — and judgment about when AI-generated logic is ready to ship
• Experience building behavioral or anomaly-based detections: establishing baselines of normal activity and engineering detections that flag meaningful deviations
• Strong log-analysis skills and demonstrated ability to distinguish malicious activity from benign noise across diverse data sources
• Clear written and verbal communication — able to document detection logic and explain coverage and trade-offs to engineers, analysts, and customers
Bonus
• Experience in an MDR, MSSP, or high-volume SOC environment
• Experience with attack simulation and validation frameworks (Atomic Red Team, purple teaming)
• Background in threat hunting or incident response across cloud environments
• Experience with UEBA platforms or statistical/ML-based detection methods (peer grouping, time-series baselining, outlier scoring)
• Experience building AI-assisted detection or investigation tooling from scratch
• Contributions to open-source detection content or the broader detection engineering community
Why Work at Artemis?
• Make a real world impact. You'll lead the human layer of defense that protects real companies. Every standard you set and process you sharpen raises the quality of protection customers depend on.
• Be challenged to be better than ever before. Our team includes some of the smartest and most driven people in the world. We guarantee you will learn more in 1 year here than 10 years in another place.
• Push the boundaries of technology. Lead a SOC built on the most advanced AI capabilities in cybersecurity, where the platform automates detection, investigation, and tuning, and your team owns the expertise, response, and relationship. You'll define what a modern, AI-native MDR looks like.…
Source: Arbeitnow (https://www.arbeitnow.fr/jobs/companies/artemis/remote-detection-engineer-19722)
We're looking for a Detection Engineer to own the detection content that powers the Artemis platform. You'll design, build, test, and continuously tune high-fidelity detections across cloud, identity, endpoint, and SaaS environments — treating detection as code, and using AI as a force multiplier at every step: authoring rules with AI assistance, and building anomaly detections that learn what's normal in each environment and flag what isn't. Detections at Artemis don't just fire alerts; they feed an AI-native investigation pipeline, so precision, rich context, and machine-readable output matter as much as coverage. This is a hands-on engineering role where every rule you ship directly determines what threats we catch for customers and how fast we catch them.
Responsibilities
• Build and maintain the detection library - Design, implement, and own high-fidelity detections across cloud (AWS, Azure, GCP), identity (Okta, Entra ID), endpoint (EDR), and SaaS log sources, from hypothesis to production.
• Practice detection-as-code - Manage detection content like software: version-controlled rules, peer review, automated validation and testing, and CI/CD deployment across customer environments.
• Map and close coverage gaps - Measure detection coverage against MITRE ATT&CK, prioritize gaps based on real-world threat activity, and systematically close them.
• Validate against real attacks - Build and run attack simulations and test harnesses to prove detections fire on true positives and stay quiet on benign activity, before and after they ship.
• Tune relentlessly - Own false-positive and false-negative rates across the fleet: analyze detection performance data, tune noisy logic at the source, and sunset detections that no longer earn their keep.
• Use AI to write detections at scale - Leverage AI throughout the detection lifecycle: use AI-assisted workflows to author, convert, test, and document rules faster than any traditional team could, and build the tooling that makes AI-generated detection content trustworthy enough to ship.
• Build behavioral and anomaly-based detections - Go beyond static signatures: establish behavioral baselines of normal activity per environment (identity, cloud, SaaS usage patterns) and engineer anomaly detections that surface deviations — impossible travel, unusual privilege use, novel API activity — with high signal and low noise.
• Engineer detections for AI-powered investigation - Design detections that produce rich, structured context so the Artemis platform can investigate and resolve cases autonomously.
• Turn intelligence into detections - Translate threat intelligence, incident findings, and threat hunt results from our research and SOC teams into durable, behavioral detection logic.
• Partner with the SOC and research teams - Close the loop with Apollo analysts and security researchers: use case outcomes and analyst feedback to drive detection improvements, and give them documentation that makes every alert investigable.
• Support customer-specific tuning - Adapt and tune detection content to each customer's environment and business context, reducing noise without sacrificing coverage.
Qualifications
• 5+ years of hands-on cybersecurity experience, with significant time in detection engineering
• Proven track record designing, building, and tuning detections at scale across SIEM, EDR, or custom detection platforms
• Strong proficiency in detection languages and formats such as Sigma, KQL, SPL, or YARA-L, and comfort writing code (Python preferred) for automation and testing
• Deep knowledge of attacker tactics, techniques, and procedures (MITRE ATT&CK) and how they manifest in logs across cloud, identity, endpoint, and SaaS telemetry
• Experience with detection-as-code workflows: Git, peer review, automated testing, and CI/CD for detection content
• Experience using AI tools to accelerate detection authoring, tuning, or validation — and judgment about when AI-generated logic is ready to ship
• Experience building behavioral or anomaly-based detections: establishing baselines of normal activity and engineering detections that flag meaningful deviations
• Strong log-analysis skills and demonstrated ability to distinguish malicious activity from benign noise across diverse data sources
• Clear written and verbal communication — able to document detection logic and explain coverage and trade-offs to engineers, analysts, and customers
Bonus
• Experience in an MDR, MSSP, or high-volume SOC environment
• Experience with attack simulation and validation frameworks (Atomic Red Team, purple teaming)
• Background in threat hunting or incident response across cloud environments
• Experience with UEBA platforms or statistical/ML-based detection methods (peer grouping, time-series baselining, outlier scoring)
• Experience building AI-assisted detection or investigation tooling from scratch
• Contributions to open-source detection content or the broader detection engineering community
Why Work at Artemis?
• Make a real world impact. You'll lead the human layer of defense that protects real companies. Every standard you set and process you sharpen raises the quality of protection customers depend on.
• Be challenged to be better than ever before. Our team includes some of the smartest and most driven people in the world. We guarantee you will learn more in 1 year here than 10 years in another place.
• Push the boundaries of technology. Lead a SOC built on the most advanced AI capabilities in cybersecurity, where the platform automates detection, investigation, and tuning, and your team owns the expertise, response, and relationship. You'll define what a modern, AI-native MDR looks like.…
Source: Arbeitnow (https://www.arbeitnow.fr/jobs/companies/artemis/remote-detection-engineer-19722)
এই তালিকা এটা পাৰ্টনাৰ ফিডৰ পৰা আহিছে। উৎস ৱেবছাইটত আবেদন কৰক।
উৎস: Artemis
Artemis-ৰ দ্বাৰা প্ৰদান কৰা তালিকা।
