Detection Engineer Recruiters

What this hire really comes down to

A Detection Engineer occupies the technical bridge between security architecture and security operations. You need someone who writes code that finds needles in your data haystack. This person stops relying on vendor defaults and builds custom detection logic that accounts for your specific environment. They understand how adversaries move through networks and how to write queries that identify those patterns early. Do not confuse this with a pure analyst role. An analyst reacts to alerts while this engineer builds the detection systems that generate those alerts. You are paying for someone who lowers your false positive rate and increases your true positive catch rate.

The scope of this role focuses on signal quality. You need someone who understands log telemetry, endpoint visibility, and cloud infrastructure data flows. If you hire someone who only knows how to configure a SIEM dashboard, you will have a pile of unmanaged alerts in a month. You need an engineer who treats detection code as a product with lifecycle management. This means version control for detections, unit testing for alerts, and continuous tuning based on real incident findings. You are looking for a practitioner who treats detection coverage as a quantifiable metric rather than an abstract goal.

What we check before you see anyone

• Detection Logic Development

  Ask them to describe a recent detection they authored from scratch. They should explain the adversary tactic they were tracking, the data source they used, and the specific query language. Look for evidence that they tested the detection against historical logs to ensure it fired without noise.

• Telemetry and Coverage Mapping

  Ask how they evaluate gaps in visibility. A solid candidate maps existing detections to the MITRE ATT&CK framework to identify blind spots. They should be able to tell you which data sources in your stack are currently underutilized and why those sources are necessary for catching specific threat types.

• Incident Response Collaboration

  Ask for an example of a detection they created following an actual security incident. They should explain how they performed a root cause analysis to determine which telemetry would have provided an earlier warning and why that detection was not already in place.

• Environment Scaling

  Ask how they handle high-volume log environments. They should explain how they balance raw data ingestion costs with the need for high-fidelity alerts. Look for technical discussions on filtering, aggregation, and data normalization strategies that keep search performance fast.

Where we find them

Look for engineers currently working in large-scale cloud environments or within established security operations centers. The best candidates have moved beyond entry-level incident response into engineering roles where they spent time automating manual tasks. You want people who demonstrate an active interest in adversary emulation, often contributing to open-source detection libraries or sharing research on technical forums.

Prioritize candidates who have worked with infrastructure-as-code and have a strong grasp of data science or analytics tools. People with backgrounds in data engineering or devops often make the jump to detection engineering successfully because they understand how to manipulate large datasets and build reliable pipelines. Motivation in this field typically stems from the technical challenge of mapping complex data structures to elusive threat patterns.

Mistakes we see

• Hiring an analyst who has never written code or performed basic automation tasks. Your hire will end up with a person who can only tweak existing dashboards rather than building new logic.

• Focusing entirely on a specific SIEM platform certification. Detection logic is transferable, but deep platform knowledge is a commodity. You want someone who understands the underlying data and logic concepts.

• Failing to ask about their experience with noisy alerts. If they cannot describe a time they had to suppress or fix a noisy detection, they likely do not understand the impact of alert fatigue on a SOC team.

The search in three steps

1. Agree the brief

   Start by defining your primary data sources. Tell candidates which SIEM or data lake tool you use so you can assess if they have the specific syntax knowledge or if they will need a ramp-up period.

2. Find and speak with people

   Include a practical evaluation component. Have them review a sample set of logs and draft a detection rule. Review their query for efficiency and their methodology for preventing false positives.

3. Introduce the people who fit

   Involve your lead incident responder in the evaluation process. They will know if the candidate understands the difference between a high-fidelity alert and a noise-heavy search.

Questions about this search

Where we fill this role

• SaaS and B2B Software
• Fintech, Payments and Insurtech
• Banking, Capital Markets and Trading
• Healthtech and Digital Health
• Health Systems, Payers and Provider IT
• PE-Backed Software

Related roles and stacks

• Cybersecurity
• CISO
• Security Engineer
• Cloud Security Engineer
• Application Security Engineer
• Security Architect
• IAM Engineer
• AWS
• Azure

Hiring guidance

Plan this hire

• Positions we recruit
• Team hiring guide
• Security Engineering Manager
• Moving from an MSP to in-house IT
• When a platform certification matters
• A technology job description that attracts the right people
• Credential checks