Top Tech Jobs & Startup Jobs

Own and improve TinyFish’s vulnerability-management program across AWS infrastructure, applications, containers, CI/CD, and production services. Implement security controls, automate security testing and compliance checks, conduct threat modeling, coordinate penetration tests, and drive findings through verified remediation. Support incident response, security logging, detection engineering, SOC 2 and ISO 27001 initiatives, and security reporting while partnering with engineering and leadership.

Design and operate AWS cloud infrastructure, improve CI/CD and deployment workflows, build internal platform capabilities, strengthen observability, automate infrastructure, and reduce developer friction. Partner with product teams, participate in incident response and postmortems, maintain Terraform infrastructure as code, support security and compliance controls, and establish scalable operational standards.

Own net-new enterprise sales to AI-native companies and large enterprises. Run complex multi-stakeholder deals end-to-end: build champions, construct business cases, negotiate multi-year contracts, manage procurement, partner with product/engineering, maintain pipeline and CRM, forecast accurately, and travel periodically for accounts and events.

Build and maintain reproducible data pipelines, experiment orchestration, CI/CD for models, Terraform-based ML infrastructure, observability, security controls, and automation to deploy and operate ML systems in production.

Lead Product Designer to define AI-native product experiences and 0→1 architectures. Design LLM-centered interaction paradigms, probabilistic UIs, and systems handling hallucination and uncertainty. Partner with product and ML engineering to influence models, create evaluation frameworks, and mentor designers to build scalable design systems and cross-functional processes.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.