# Member of Technical Staff (Offensive Security Engineer) at Perplexity > Remote · United States · Staff · Security · open. Source: https://alderhq.app/jobs/ashby%3Aperplexity%3A69fd6a56-0050-44f7-9ed2-2c3a7320908d (read 2026-11-06). ## Facts (observed) - Company: [Perplexity](https://alderhq.app/companies/perplexity) - Location text: San Francisco; Remote (United States); London; Belgrade; New York City - Where it can be done from (inferred): Remote · United States (evidence: "Location: San Francisco; Remote (United States); London; Belgrade; New York City") - Posted: 2026-04-02 (218 days ago) - First seen by alder: 2026-11-03 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/perplexity/69fd6a56-0050-44f7-9ed2-2c3a7320908d - Skills listed (inferred): Python, Go, AWS, GCP, Azure, Kubernetes, Docker, LLMs ## Pay and sponsorship - Posted pay: $220k–$405k per year (from the listing's pay field) - Market band for similar posted roles (SF Bay Area, n 100): p25 $223k, median $250k, p75 $289k ## Description (the employer's text) Perplexity is seeking a highly skilled, experienced and hands-on Offensive Security Engineer to join our dynamic security team, taking an adversarial approach to hardening Perplexity's infrastructure, applications, and AI systems. You'll plan and execute red team operations, penetration tests, and attack simulations across our cloud infrastructure, web and mobile applications, AI/ML pipeline, and corporate environment—finding real vulnerabilities before adversaries do and working directly with engineering teams to drive remediation. ### Responsibilities Plan and execute red team and purple team engagements simulating advanced threat actors across cloud infrastructure (AWS, Kubernetes), endpoints, and application surfaces Conduct continuous penetration testing of web applications, APIs, mobile clients, browser extensions, cloud infrastructure, and internal services Assess AI/ML-specific attack surfaces including prompt injection, model exfiltration, agent abuse, tool-use exploitation, and MCP security boundaries Develop and maintain custom offensive tooling, exploits, and automation to improve the efficiency and coverage of security testing Perform open-scope adversary simulations that test detection and response capabilities end to end, collaborating closely with the defensive security team Drive threat modeling sessions with engineering teams to identify and prioritize attack vectors in new features and architectures Deliver clear, actionable findings to both technical and executive audiences; partner with engineering to validate remediations Contribute to the security of CI/CD pipelines, supply chain integrity, and secrets management through offensive assessment Stay current on emerging attack techniques, vulnerability research, and adversary tradecraft; bring external perspective into Perplexity's security strategy ### Qualifications 5+ years of hands-on experience in offensive security, red teaming, or penetration testing Deep technical expertise in at least two of: cloud security (AWS/GCP/Azure), web/API application security, Kubernetes and container security, macOS/Linux endpoint security, network penetration testing, or CI/CD pipeline security Track record of discovering impactful vulnerabilities or developing novel attack techniques in production environments Strong programming and scripting skills in Python, Go, or similar languages; comfortable writing custom tooling and exploits Experience with industry-standard offensive tools (Burp Suite, Cobalt Strike / Sliver / Mythic, Metasploit, BloodHound, nuclei, etc.) and ability to operate beyond them Excellent written and verbal communication; able to translate complex technical findings into clear risk narratives Experience assessing AI/ML systems, LLM applications, or agentic workflows for security vulnerabilities Bonus: Published security research, conference talks (DEF CON, Black Hat, BSides), CVE credits, or meaningful bug bounty contributions --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Aperplexity%3A69fd6a56-0050-44f7-9ed2-2c3a7320908d and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.