Jobs at Cogent Security

Lead end-to-end pipeline generation across field, channel, digital, partner, and SDR teams. Build and scale demand programs (ABM, outbound, events, inbound, paid), define lead-to-SQL model, track funnel metrics, partner with Sales/RevOps/Finance/Partnerships, and run weekly optimization loops. Hire and develop a demand team and launch integrated plays to scale qualified enterprise pipeline.

Lead sales enablement for B2B software: build onboarding and certification, create curriculum and sales assets, mine Gong and field feedback, drive tool adoption (HubSpot, Gong, Notion), and measure impact on ramp, pipeline progression, and POV quality.

Manage day-to-day operations across workplace (SF & NY), people operations (recruiting coordination, onboarding, legal/immigration coordination, Founder Academy), events (concept to execution), and special projects with founders and Head of BizOps. Drive cross-functional initiatives, vendor and landlord relationships, swag and off-sites, and process automations using AI tools and scripts.

Manage day-to-day operations of the San Francisco office and coordinate logistics for the New York office. Oversee move-ins/outs, vendor relationships, supplies, shipping, visitor check-in, onboarding logistics, offsite planning, and employee experience programs. Act as primary office contact across teams and locations to ensure smooth operations.

As a Technical Account Manager, you will oversee customer deployments, ensuring technical success and integration, all while building strong relationships and troubleshooting issues effectively.

Build and scale backend services and integrations for autonomous AI agents. Design distributed, stateless and stateful systems, APIs, and infrastructure for reliability, security, and enterprise integration. Drive scalability, CI/CD, container orchestration, multi-cloud deployments, and mentor growing engineering teams.

Build and own Cogent's full‑stack AI security product experience: design, implement, and maintain backend microservices, APIs and databases; develop frontend interfaces (customer portal, knowledge engine, labeling tool, dashboards); integrate systems; ship features in a multi‑tenant/cloud environment; mentor hires and contribute to engineering, operational excellence, and hiring processes.

Lead frontend architecture and platform work, build reusable component libraries and tooling, deliver AI-driven user features for security workflows, mentor engineers, and ensure scalable, high-quality frontend infrastructure and UX.

Design and build agentic AI systems for cybersecurity: architect AI cyber taskforce and production-grade agentic components, implement ranking/retrieval/search powered by LLMs, design training/evaluation frameworks, decompose security workflows, address scale/performance, and mentor engineers while contributing to engineering and operational excellence.

Early-career research-engineering fellowship to develop agentic security and auto-remediation: prototype research at the intersection of AI and formal methods, build production systems, partner with engineers and security teams, and create benchmarks and evaluation harnesses for verified-correct, policy-compliant behavior.

Design and implement a scalable data platform and integration pipeline to ingest, normalize, and index enterprise data. Build connectors, ETL/streaming pipelines, and storage/indexing strategies to support semantic search and GenAI use cases. Partner with applied AI teams, make build-vs-buy decisions, and create reusable patterns to scale integrations.

Own and build the software delivery lifecycle and CI/CD/platform systems that enable engineers and autonomous agents to build, test, deploy, and verify code securely. Implement self-hosted builders, secure GitHub Actions Runner alternatives, and infrastructure provisioning solutions.

Build and optimize data platform storage (ClickHouse, Postgres), enable on-prem deployments for enterprise customers, harden security systems, create an agent-first infrastructure and platform layer, and lead large-scale infrastructure projects across stakeholders.

Own storage, protection, and operations for relational, streaming, and analytical stores. Standardize backup, restore, retention, and encryption across Aurora/RDS, ClickHouse, and MSK. Build observability dashboards for capacity, performance, replication, lag, and cost. Create a Storage Operations Agent for incident triage, slow-query investigation, and remediation workflows. Hands-on engineering role focused on data infrastructure, automation, and agent-forward operations.

As a Research Scientist at Cogent, you will conduct high-impact research in AI-driven code analysis and automated reasoning, publish findings, and collaborate with product teams.

As an AI Research Engineer, you'll conduct research in AI and automated reasoning, creating innovative solutions, testing systems, and contributing to scientific publications while collaborating with engineering teams.

Own product security across the SDLC: threat modeling, secure design reviews, application security testing (code review, SAST/DAST), supply-chain/dependency hardening, CI/CD security, and building automated security tooling and guardrails while partnering with engineering and product.

Lead security engineering for an AI-native cybersecurity product: architect product security, build and evolve operational security and incident response, collaborate with ML engineers to integrate security into AI agents, implement protections and automation, and represent Cogent externally through writing and speaking.

Own and harden corporate security for endpoints, identity, and SaaS. Implement Zero Trust and device-trust patterns, build automation and tooling, run detection/response for enterprise systems, and serve as the internal security SME for corporate workflows.

Design and scope vulnerability management solutions for enterprise customers, translate customer environments into implementation plans, write actionable tickets for engineering, own technical relationships during deployments, and create repeatable scoping practices to reduce forward-deployed engineering.