Top Tech Jobs & Startup Jobs

Lead architecture, automation, and ecosystem integration for Treasury systems: design a treasury data foundation, evaluate/implement TMS or internal builds, automate cash and payment workflows (Claude-powered), ensure SOX-compliant controls, and partner across Treasury, Finance, Engineering, banks, and vendors. Manage roadmap, vendor relationships, and unblock one to two finance systems engineers while driving projects from design through production.

Embed with recruiting teams to enable AI-assisted hiring: teach and codify recruiter-built LLM skills, provide technical support, build fast pilots and prototypes, create documentation and enablement programs, and collaborate with People Products and governance to productionize successful workflows.

Own vision, strategy, roadmap, and execution for research-driven AI products. Partner with research and engineering to productize models, identify high-potential use cases, synthesize user insights, and ship model capabilities that solve real-world problems.

Provide end-user IT support across hardware, software, networking, and accounts (primarily macOS), manage onboarding/offboarding and access workflows, maintain documentation and runbooks, troubleshoot devices and AV/conference systems, participate in on-call rotation, and automate operational tasks using scripting and tools to improve scale and reliability.

Lead technical delivery and configuration of business systems, translate business requirements into technical specifications, manage vendor evaluations, design automation and integrations (APIs/iPaaS), document processes, conduct testing and UAT, provide end-user training and support, and monitor system performance to drive operational efficiency across the organization.

Build and maintain scalable data pipelines, warehouses, and dashboards to support safety monitoring, abuse detection, and enforcement. Integrate multi-source data, implement data quality and governance, enable ML model monitoring, and provide self-service tooling for Safeguards stakeholders.

Build and scale infrastructure and data pipelines for Safeguards ML research. Own training, evaluation, and scoring workflows, design researcher-facing tooling, ensure correctness and reliability, productionize high-value research workflows, and improve throughput, cost, and reliability of large-scale inference and scoring workloads while partnering with researchers.

Lead revenue accounting, deal desk, and technical accounting: set ASC 606 positions, approve contract accounting, drive revenue systems (Zuora), design controls, prepare disclosures, influence Sales/Legal/Engineering, and grow the team toward public-company readiness.

Drive user acquisition, engagement, retention, and monetization by building full‑stack growth features, designing and running A/B experiments, analyzing user data, and collaborating with product, marketing, and data teams to scale AI products.

The role involves owning the technical strategy for developer productivity, designing reliable distributed infrastructure, and leading complex developer infrastructure projects.