• Define product strategy, roadmap, and execution for AI-driven onboarding and operational product experiences in close partnership with business stakeholders and cross-functional teams • Drive the full product lifecycle from discovery and experimentation through launch and iteration, ensuring solutions deliver measurable customer and business outcomes • Translate complex customer needs, technical capabilities, and market opportunities into clear priorities, comprehensive product requirements, and actionable user stories that guide high-quality execution • Lead alignment across Design, Engineering, Data Science, AI/ML, Sales, and Marketing to remove blockers, resolve strategic issues, and keep delivery on track • Measure success through KPIs, customer impact, and financial outcomes while crafting a compelling multi-year vision for scalable, intelligent product experiences

• Develop and implement automated testing strategies, ensuring efficiency and coverage in QA processes. • Support the QA team in creating and evolving automation frameworks and best practices. • Design test cases and automated scripts for functional and non-functional validation. • Execute integration, regression, and acceptance tests, ensuring the quality and stability of deliverables. • Analyze results and report quality metrics, contributing to data-driven decisions. • Identify defects and propose technical solutions that promote continuous improvement of software quality.

• Desenvolver e manter aplicações back-end utilizando Node.js, seguindo boas práticas de arquitetura e código limpo. • Atuar no desenvolvimento de interfaces e integrações utilizando React e TypeScript. • Criar, manter e otimizar pipelines de CI/CD, garantindo automação de builds, testes e deploys. • Trabalhar com Docker para containerização de aplicações e padronização de ambientes • Criar e manter arquivos de configuração em YAML (pipelines, infraestrutura ou automações). • Gerenciar versionamento de código e fluxo de trabalho utilizando GitHub, incluindo GitHub Actions. • Colaborar com práticas de DevOps, contribuindo para a confiabilidade, escalabilidade e observabilidade das soluções. • Apoiar decisões técnicas, revisão de código e boas práticas de desenvolvimento.

Role Description Cerebras Systems Inc. has multiple openings for Sr. Member of Technical Staff. - Design and develop software features that support system resiliency and high availability, including automated recovery mechanisms and fault-tolerant architecture across distributed environments. - Develop and maintain cloud-based deployment workflows for AI inference software using AWS tools and services to support low-latency and scalable system performance. - Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks. - Use parallel programming techniques (e.g., multi-threading, asynchronous processing) to maximize resource efficiency on AWS compute instances. - Develop software components to support visualization and analysis of system performance metrics, enhancing the monitoring and usability of inference services. - Develop inference software in Docker containers and define Kubernetes orchestration strategies that ensure software reliability and efficient scaling. - Develop automated scripts to detect and mitigate common failure modes, improving software system reliability. - Debug issues related to model deployment, container orchestration, networking configurations, documenting steps to reproduce and root-cause defects. - Triage and resolve defects in the software service by analyzing logs, metrics, and distributed traces using tools like AWS CloudWatch, Grafana, or custom Python scripts. - Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging. - Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers. - Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability. Qualifications - Master’s degree or foreign equivalent degree in Computer Science, or a related field. - 18 months of experience as Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or a related occupation. Requirements - Infrastructure-as-Code and deployment automation: Terraform, AWS CloudFormation, AWS CDK, and Ansible. - Containerization and orchestration: Docker, Kubernetes, AWS EKS, AWS Elastic Container Service (ECS), AWS Fargate, and Helm. - Compute and serverless services: AWS EC2, AWS Lambda functions, and Auto Scaling Groups. - Monitoring, logging, and distributed tracing: AWS CloudWatch, AWS X-Ray, ELK (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana. - Programming languages and frameworks: Python, Node.js, JavaScript, and Flask. - Data storage and caching: PostgreSQL, Redis, and NFS. - CI/CD and version control: Jenkins and Git. Benefits - Salary Range: $230,000.00 per year to $250,000.00 per year. - Telecommuting permitted. Company Description Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. - Current customers include top model labs, global enterprises, and cutting-edge AI-native startups. - OpenAI recently announced a multi-year partnership with Cerebras to deploy 750 megawatts of scale. - Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.