Senior Research Engineer, Threat Intelligence

SecurityScorecard; Ottawa; On-site; CAD 127,500 - 162,500; Full time

Benefits offered by this job

Stock options

Health benefits

Unlimited PTO

Parental leave

Tuition reimbursements

Job summary

SecurityScorecard is seeking an engineering counterpart for their STRIKE Threat Intelligence team. This role involves turning research artifacts into usable tools for threat detection and customer alert mechanisms, working closely with R&D leadership.

Candidates should have 5-8 years of experience in engineering with exposure to cybersecurity and threat intelligence. Familiarity with Python, AWS, and detection tooling is essential. The position offers a competitive salary package with various benefits including health coverage and unlimited PTO.

Qualifications

• 5 to 8 years in a hands-on engineering role with exposure to threat intelligence.
• Experience building production systems for threat intel data is required.
• Self-taught practitioners with strong public work are welcome.

Responsibilities

• Own path from research output to production-ready artifact.
• Build and maintain STRIKE platform components across multiple services.
• Drive STIX 2.1 adoption as a unified output schema.

Skills

Python

TypeScript/Node

Relational and cache data stores

Cloud infrastructure

STIX 2.1

TAXII 2.1

YARA

Sigma

Education

Bachelor’s or Master’s in Computer Science, Cybersecurity, or related field

Tools

AWS

Containers

CI/CD pipelines

Job description

About the Role

You’ll join STRIKE, SecurityScorecard's Threat Intelligence team, as the engineering counterpart to research. STRIKE runs several research motions in parallel, each on its own clock: rapid response to active events, longer product-tied work, and standards-anchored research on a quarterly cadence. The path from a finding to a shipped detection or feed gets reinvented every time. That’s the problem this role is here to solve.

You’ll work directly with the senior technical leader who owns STRIKE’s R&D direction, and report to the Head of Threat Research for people management. Technical direction comes from R&D leadership; you own delivery. You take a research artifact (a malware finding, an infrastructure cluster, a new indicator class, a behavioral pattern) and turn it into something the company can use without a second round of engineering: schemas, pipeline hooks, distribution feeds, detection rules, or platform APIs.

This isn’t a pure research role, and it isn’t a pure platform role either. Researchers ideate, you ship.

Key Responsibilities

• Own the path from research output to production‑ready artifact: a detection rule, a distributed feed, a scoring input, or a customer alert. Partner with adjacent teams to define clean handoff contracts, so new signals arrive downstream with the schema, value framing, and consumption pattern already defined.
• Build and maintain STRIKE platform components across multiple services and runtimes, including distribution servers, sandbox orchestration, OSINT ingestion, federated sharing endpoints, agent runtimes, and rules engines that operate over standards‑anchored predicates. Extend these systems without breaking the data contracts already in production.

Detection Content and Signal Production

• Turn research into shipped detection content: YARA, Sigma, STIX patterns, behavioral indicators, and the pipelines that distribute them. Build correlation pipelines that link scan data, attack surface signals, vulnerability data, and adversary tracking into customer‑facing intelligence.

Data Model and Standards Adoption

• Drive STIX 2.1 adoption as a unified output schema and TAXII 2.1 as a distribution standard. Define and govern schemas that hold up once they reach downstream teams.

Research Workflow Engineering

• Build the automation that removes commodity overhead from research work: indicator enrichment, report drafting, corpus correlation, feed normalization, and sandbox triage. Help move the team from analyst‑driven, model‑assisted workflows toward model‑driven workflows with analyst review.
• The work that matters most here is often the unglamorous part: retrieval grounded in the team’s own corpus so outputs cite sources rather than model priors, schema‑constrained output so a generated indicator is a valid one, and eval harnesses that catch regressions before analysts do. Cost accounting, latency budgeting, prompt versioning, and output logging round out the infrastructure that makes a workflow safe to run unattended.
• You should have a clear sense of when a model is the wrong tool. A regex beats a model for known patterns; a SQL query beats a model for structured data. Knowing where that line sits, and respecting it, is part of the job.

Cross‑Functional Delivery

• Coordinate with engineering, measurement, and platform product teams so research actually lands in product. You’ll often serve as the engineering voice translating between researchers, product managers, and platform engineers, and you may occasionally explain the work to customers, journalists, or executives.

Qualifications

Education: Bachelor’s or Master’s in Computer Science, Cybersecurity, or a related technical field. Self‑taught practitioners with strong public work are welcome.

Experience: 5 to 8 years in a hands‑on engineering role with meaningful exposure to threat intelligence, security research, or detection engineering. Prior experience building production systems that consume or emit threat intel data is required.

Technical Skills

• Python and TypeScript/Node at a production level
• Relational and cache data stores, plus at least one streaming or batch data platform
• Cloud infrastructure (AWS preferred), containers, and CI/CD pipelines
• Working knowledge of STIX 2.1, TAXII 2.1, MISP, and MITRE ATT&CK, and how they work together in practice

Detection and Research Tooling

Hands‑on experience with YARA, Sigma, and STIX Patterning. Comfortable reading malware analysis output, parsing adversary infrastructure data, and writing detection logic that holds up under production load.

Applied Language Models

You’ve shipped production systems that use language models, not just demos. That includes retrieval over a real corpus, structured output with schema validation, eval harnesses that catch regressions before users do, and a solid understanding of where models fail: recency, long‑tail facts, numerical reasoning, and adversarial input or prompt injection. You can do the cost‑per‑task math for your workloads, and you can make the case when a smaller, tightly scaffolded model beats a larger one. You approach model output with healthy skepticism by default. The bar for shipping a model‑generated indicator or detection is higher than for shipping a regex, and you understand why and design accordingly.

Bridge Mindset

You write code that ships, and you understand why researchers think the way they do. If you’ve only ever worked from a backlog handed down by a product manager, this probably isn’t the right fit. If you’ve taken an idea sketched out in a chat message and turned it into a deployed pipeline before the next sprint began, that’s the mode we’re looking for.

Bonus

• Experience with policy‑as‑code or expression‑language engines (CEL, OPA, or similar)
• Published or co‑authored security research (campaigns, vulnerabilities, adversary tracking)
• Large‑scale telemetry experience (Splunk, Kinesis, NetFlow, or equivalent)
• Contributor or maintainer on open‑source threat intel projects (MISP, OpenCTI, Sigma, STIX, ATT&CK)
• Familiarity with quantitative risk frameworks such as FAIR
• Familiarity with Golang at a production level

Specific to each country, we offer a competitive salary, stock options, health benefits, and unlimited PTO, parental leave, tuition reimbursements, and much more!

The estimated total compensation range for this position is $127,500 - $162,500 CAD (base plus bonus). Actual compensation for the position is based on a variety of factors, including, but not limited to affordability, skills, qualifications and experience, and may vary from the range. In addition to base salary, employees may also be eligible for annual performance‑based incentive compensation awards and equity, among other company benefits.

SecurityScorecard is committed to Equal Employment Opportunity and embraces diversity. We believe that our team is strengthened through hiring and retaining employees with diverse backgrounds, skill sets, ideas, and perspectives. We make hiring decisions based on merit and do not discriminate based on race, color, religion, national origin, sex or gender (including pregnancy) gender identity or expression (including transgender status), sexual orientation, age, marital, veteran, disability status or any other protected category in accordance with applicable law.

We also consider qualified applicants regardless of criminal histories, in accordance with applicable law. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact [e-mail].