Jobs at Robinhood

Lead security incident responses, build and maintain detection engineering frameworks across cloud and Kubernetes environments, and architect AI-driven Autonomic Security Operations capabilities. The role involves analyzing multi-language codebases, identifying vulnerabilities, tuning detection pipelines, developing SOAR playbooks, communicating with executives during high-pressure incidents, and participating in a weekly on-call rotation.

Lead end-to-end product design for AI-powered agentic trading experiences, from early concepts through launch. Collaborate with product managers, engineers, researchers, creative teams, and brokerage leadership to define product direction, create prototypes, simplify complex financial and AI concepts, and establish shared interaction patterns. Use LLMs and AI-assisted tools in the design workflow while ensuring products meet quality, regulatory, usability, and user-trust standards.

Lead architecture and delivery of scalable AI infrastructure, including model serving, feature stores, training systems, and ML observability. Partner with ML, data, and AI teams to improve workflows and reliability. Manage AWS CPU/GPU resources, establish monitoring standards, shape technical strategy, and mentor engineers. The role requires deep expertise in distributed systems, production ML workflows, search systems, vector databases, and modern ML infrastructure tooling.

Support Robinhood’s Offensive Security team by testing AI services, models, pipelines, cloud and Kubernetes environments, macOS systems, and smart contracts. The intern will identify and exploit vulnerabilities, build security infrastructure and tooling, and contribute to the maturity of the company’s offensive security program. The role requires in-person attendance at least three days per week in Bellevue or Menlo Park.

Build a scalable AI security platform, foundational services, APIs, SDKs, and guardrails for AI-powered security agents. Design secure, reliable distributed systems incorporating identity, authentication, authorization, encryption, and data protection. Partner with security and engineering teams to deliver reusable platform capabilities, improve performance and developer experience, and shape the platform’s technical architecture. The role requires hands-on software engineering experience with AI platforms, cloud-native infrastructure, and large-scale systems.

Leads red team operations, penetration testing, threat modeling, and adversarial simulations across applications, infrastructure, corporate, and physical environments. Develops security-testing tools, partners with detection and response teams, communicates and remediates findings, leads related incidents, and mentors offensive security engineers. The role requires advanced knowledge of cloud, containers, defensive evasion, identity security, network protocols, and MITRE ATT&CK, along with Python, Go, and JavaScript proficiency.

Design, build, and operate distributed data streaming platforms and real-time event processing systems. Scale and secure pipelines using technologies like Kafka, Flink, and Debezium, collaborate with product, data, and ML teams, and improve developer experience through tools and documentation. Mentor engineers and drive architectural decisions for long-term platform reliability.

Backend software engineering intern responsible for owning a high-impact project from scoping through production launch. Duties include designing, building, testing, releasing, maintaining, and scaling backend services and codebases using Python/Django, Go, PostgreSQL, Kafka, Redis, Memcached, AWS, and Kubernetes. The intern will collaborate cross-functionally, work with a mentor, and develop software meeting financial-platform correctness and scalability requirements.

Set technical strategy and architecture across security engineering domains, build AI security foundations, and lead cross-cutting initiatives from concept through production. The role requires hands-on development and operation of production security systems, deep IAM or cryptography expertise, broad security engineering knowledge, cross-organizational influence, ambiguity management, collaboration, and mentorship.

Design, build, and ship end-to-end personalization, ranking, and recommendation systems; prototype and scale new ML capabilities (including LLM fine-tuning and agentic workflows); partner with product and engineering to define strategy and deploy models to production at scale; lead architecture and code reviews, mentor engineers, and drive technical direction in a regulated fintech environment.

The Machine Learning Engineer will implement and evaluate ML algorithms, focusing on model development, A/B testing, and cross-functional collaboration to drive innovative solutions for financial challenges.

Own the architectural evolution of core infrastructure across service mesh, Kubernetes compute, and Terraform provisioning. Lead multi-region platform strategy, improve reliability and developer autonomy, diagnose issues at source-code and protocol levels, contribute upstream when appropriate, and drive technical alignment across engineering teams through architecture proposals and design reviews.

As a Staff Software Engineer on the Storage Platform team, you will design distributed storage systems, improve database reliability and performance, build automation for database management, and ensure high availability for user-facing products.

Design, implement, and operate core distributed storage infrastructure for Postgres, NoSQL, and caching at scale. Lead sharding, query routing, proxy services, connection pooling, multi-region failover, observability, and control-plane automation to improve availability, performance, and cost efficiency.

Design, build, and maintain enterprise security tooling and AI safety guardrails. Secure identity systems, endpoints, and telemetry; automate GRC evidence gathering; support vulnerability management; defend against advanced threats and collaborate cross-functionally to maintain enterprise security posture.

Lead and execute incident response, build and tune global detection pipelines for cloud and Kubernetes, architect AI-native Autonomic Security Operations, analyze multi-language code for vulnerabilities, mentor engineers, and participate in on-call rotations.

Design and build backend services and secure data pipelines to protect customer data. Implement token issuance, authentication, anonymization, data retention/deletion (CCPA/GDPR), and monitoring/auditing. Collaborate with access management, infrastructure, and data teams to enforce least-privilege controls and enable secure AI-driven product capabilities.

Lead and execute red team exercises and penetration tests across applications, infrastructure, and physical environments. Mentor teammates, develop automation tools, partner with detection/response teams, prioritize and drive remediation, and conduct adversarial simulations to improve detection and incident readiness.

Design, build, and operate scalable cloud networking and service mesh infrastructure on AWS/EKS. Lead traffic management, service discovery, Istio/Envoy deployments, API/versioning standards, IaC with Terraform, and developer tooling in Python/Go while partnering with security and application teams and mentoring engineers.

Design, build, and operate a scalable, highly available Kubernetes-powered container platform. Lead migration of core workloads to Amazon EKS, optimize container lifecycle management and networking, implement multi-region cluster provisioning and integrations (service mesh, auth, load balancing), and troubleshoot production performance to improve platform reliability and uptime.