Top Tech Jobs & Startup Jobs

Supports the CEO by managing calendars and inboxes, preparing daily briefs and meeting materials, tracking action items, coordinating travel and office logistics, welcoming visitors, handling errands, and serving as a trusted point of contact. The role requires strong organization, discretion, communication, prioritization, independence, and proficiency with productivity tools.

Owns full-cycle recruiting and hiring strategy, with a focus on software engineering and technical roles. Responsibilities include sourcing, screening, interviewing, closing, onboarding, offboarding, hiring-manager partnership, employer branding, talent marketing, funnel metrics, and recruiting-process improvements. The role also provides basic employee-facing support on people policies and operates with substantial autonomy while using AI tools to improve recruiting efficiency.

The job description provides no specific responsibilities or qualifications beyond seeking a Senior SDET. The role appears to involve software quality assurance and testing, but detailed duties are listed only as placeholders.

Own an AI platform product area end to end, from business case and discovery through prototyping, roadmap decisions, customer validation, and measurable outcomes. Conduct research with property management customers, define model quality evaluations, prioritize engineering capacity, build working prototypes using AI tools, collaborate directly with engineers and codebases, and establish success metrics for product initiatives.

Own the reliability, scalability, security, and cost optimization of AWS infrastructure across current and next-generation SaaS platforms. Build infrastructure as code, evolve CI/CD pipelines, improve observability, lead incident response and root-cause analysis, embed security practices, support compliance, and mentor engineers. Partner with software and data architects to establish new platform infrastructure while maintaining production systems.

Build and maintain scalable backend services, APIs, and data flows for current and next-generation SaaS platforms. Guide backend architecture and service standards, resolve performance and reliability issues, and contribute to production AI and LLM capabilities. Mentor engineers through reviews and technical guidance, strengthen testing, observability, deployment, and operational practices, and collaborate with architecture, product, data, and platform teams on technical direction and delivery.

Lead frontend architecture and hands-on development across current and next-generation SaaS platforms. Establish standards for component architecture, state management, performance, testing, accessibility, and maintainability. Build AI-enabled interfaces involving chat, streaming, and agentic workflows; integrate APIs and real-time data; resolve frontend reliability issues; mentor engineers; and influence technical direction across product, design, and engineering teams.

Lead and scale onboarding, training, support, and review operations teams. Create operating systems, SOPs, QA, SLAs, staffing and workforce models. Partner cross-functionally to improve customer experience, adopt AI/automation, and deliver measurable operational leverage while building manager capability and performance systems.

Own the architectural vision for a multi-tenant SaaS platform while remaining hands-on. Lead backend and frontend system design, cloud and DevOps architecture, technology decisions, scalability, security, observability, reliability, and cost optimization. Partner with a Staff Data Architect to build a next-generation platform, guide migration from the existing system, evaluate AI and LLM technologies, align technical roadmaps with business goals, and mentor engineering teams through architecture reviews and hands-on collaboration.

Own the end-to-end architecture of Opiniion’s data platform, including ingestion, transformation, storage, semantic layers, governance, lineage, and quality. Partner with the Staff Software Architect on a new platform while evolving the existing foundation. Design data models and statistical insights, support BI and AI/ML use cases, guide platform investments, and mentor data engineers. The role is hands-on and requires strong Databricks, SQL, Python, distributed processing, cloud, and modern data architecture expertise.