Harness

Security Research Engineer - Detection Engineering

Harness Bengaluru, Karnataka, India 2 days ago
engineering

Harness is led by technologist and entrepreneur Jyoti Bansal, founder of AppDynamics (acquired by Cisco for $3.7B). The company has raised ~$570M in Series E venture funding, is valued at $5.5B, and backed by top investors including Goldman Sachs, Menlo Ventures, IVP, Google Ventures, J.P. Morgan, Capital One Ventures, Citi Ventures, ServiceNow, Splunk Ventures and more. Harness is building the industry’s leading AI-powered software delivery platform, enabling teams worldwide to build, test, and deliver software faster, safer, and more reliably. Writing code is only 30–40% of the engineering lifecycle — the rest involves testing, deployments, security, compliance, and optimization. Harness brings AI and automation to this outer loop, turning complex, time-consuming workflows into streamlined processes at massive global scale.

The platform includes industry leading products in CI/CD, Feature Flags, Cloud Cost Management, Service Reliability, Chaos Engineering, Software Engineering Insights, Internal Developer Experience, and API discovery, observability, governance, and runtime protection. Over the past year, Harness powered 128M deployments, 81M builds, 1.2T API calls protected, and $1.9B in cloud spend optimized, helping customers like United Airlines and Choice Hotels accelerate releases by up to 75% and achieve 10x DevOps efficiency. With employees in over 25 countries, Harness is shaping the future of AI-driven software delivery — and we’re looking for exceptional talent to help us move even faster.

Key Responsibilities

  • Develop, optimize, and maintain detection rules and signatures for all detection and edge defences.
  • Develop context-enriched detections by leveraging user behavior analytics, traffic fingerprints, and API interaction context.
  • Build and enhance Bot detection logic, identifying automated threats such as credential stuffing, scraping, API abuse, and fraud automation.
  • Create correlation logic that combines multiple weak indicators (behavioral, request, session, and IP signals) into high-confidence detections.
  • Research, design, and codify detections for the OWASP Top 10, OWASP API Top 10, and bot-driven attack vectors.
  • Analyze large-scale security event telemetry to identify detection gaps, optimize existing rules, and reduce false positives.
  • Collaborate with Engineering and Data Science teams to operationalize detection intelligence into Traceable’s engines.
  • Continuously tune and validate detection rulesets based on real-world traffic, diverse customer environments, and evolving attacker behaviors.
  • Build automation pipelines and validation frameworks to test detection logic and correlation performance.
  • Investigate false positive/negative trends, and contribute to detection precision metrics.
  • Analyze CVEs and emerging vulnerabilities, build proactive defenses, and publish research blogs or advisories based on findings.
  • Contribute to product-level improvements by feeding back research insights into feature design and detection capabilities.

 

Required Skills & Experience

  • 1 - 4 years of experience in security research, detection engineering.
  • Strong background in WAF/WAAP detection, Bot detection.
  • Hands-on experience writing rule logic:
    • Coreruleset experience
    • Deep understanding of regex
  • Deep understanding of HTTP, API protocols, and common web attack payloads (XSS, SQLi, SSRF, Command Injection, Deserialization, etc.).
  • Deep understanding of API Attack methodologies including OWASP API Top 10.
  • Knowledge of GraphQL, gRPC and other protocols.
  • Working knowledge of Bot behavior analysis, traffic fingerprinting, anti-automation, and CAPTCHA evasion tactics.
  • Strong analytical ability to review false positives/negatives, perform event triage, and fine-tune detection coverage.
  • Familiarity with API abuse detection, authentication attacks, and session-based correlation logic.
  • Experience leveraging machine learning models or heuristic scoring for anomaly detection.
  • Experience with writing signatures for any product.
  • Experience building or tuning detection for OWASP Top 10 and API Top 10 categories.
  • Understanding of alert workflows, and signal correlations.
  • Proficiency in Java and Python for prototyping and automating rule validation workflows.
  • Excellent communication, documentation, and cross-functional collaboration skills.

Nice to Have

  • Contributions to open-source security projects, especially those related to the OWASP Top 10 or OWASP API Top 10.
  • Experience developing custom WAF/WAAP rule engines, threat classifiers, or signal correlation pipelines.
  • Background in API security, runtime protection, or detection engineering at scale.
  • Authored publications, technical blogs, or delivered conference talks.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin.

Note on Fraudulent Recruiting/Offers

We have become aware that there may be fraudulent recruiting attempts being made by people posing as representatives of Harness. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers. 

Please note, we do not ask for sensitive or financial information via chat, text, or social media, and any email communications will come from the domain @harness.io. Additionally, Harness will never ask for any payment, fee to be paid, or purchases to be made by a job applicant. All applicants are encouraged to apply directly to our open jobs via our website. Interviews are generally conducted via Zoom video conference unless the candidate requests other accommodations.

If you believe that you have been the target of an interview/offer scam by someone posing as a representative of Harness, please do not provide any personal or financial information and contact us immediately at security@harness.io. You can also find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commission’s website (https://consumer.ftc.gov/articles/job-scams), or you can contact your local law enforcement agency.

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