Top Tech Jobs & Startup Jobs

Architect and improve enterprise SaaS platform availability, resilience, scalability, performance, and cost efficiency. Define measurable production-readiness, capacity, recovery, and performance requirements; design failover and recovery mechanisms; eliminate bottlenecks and single points of failure; lead testing and remediation; optimize AI model usage and infrastructure economics; and drive architecture execution across Engineering, Cloud Infrastructure, DevOps, QA, and AI teams.

Lead procurement strategy and execution, manage vendor negotiations and contract lifecycle, run RFP/RFI and deal processes, partner with product and engineering to design AI-enabled procurement solutions, support sales and client engagement, and own cross-functional workstreams and vendor onboarding.

Owns tax accuracy, quality, and performance for AI-powered Sales and Use Tax products. Translates complex indirect tax requirements into product specifications, testing frameworks, quality standards, and roadmap priorities. Partners with product, engineering, QA, and customer-facing teams to launch capabilities, analyze failures, address tax risks, and improve customer outcomes. Requires deep multistate sales and use tax expertise, strong analytical judgment, and cross-functional communication skills.

Lead client-facing strategic delivery for enterprise AI initiatives. Responsibilities include understanding customer priorities, facilitating workshops, defining AI use cases, developing deployment roadmaps, evaluating value and feasibility, tracking KPIs, aligning stakeholders, coordinating technical execution, supporting adoption and change management, and translating customer feedback into product improvements.

Lead enterprise AI transformation strategy and value realization across finance, tax, risk, governance, and compliance functions. Conduct discovery, define deployment roadmaps, prioritize use cases, establish KPIs, engage executive stakeholders, align initiatives with control frameworks, and guide deployment engineers during rollout. Translate complex regulated workflows into responsible, scalable AI implementations and contribute insights to product and engineering teams. Travel may be required for customer engagements and workshops.

Lead the security architecture and implementation for an enterprise AI platform: secure cloud infrastructure, data protection, IAM, tenant isolation, and GenAI workflows. Embed security into CI/CD, IaC, containers, secrets management, and operations. Design secure customer deployment patterns, support enterprise security reviews, and partner on compliance (SOC 2, ISO 27001, SSPA) while personally implementing critical security capabilities and guiding cross-functional engineering teams.

Lead product strategy and execution for AI-powered enterprise products. Drive development from zero to one and establish product processes.

The Senior GenAI Engineer will design, develop, and deploy scalable GenAI applications using Python and cloud technologies, primarily on Azure. Responsibilities include leading GenAI development, optimizing large language models, and mentoring junior developers.

This role involves managing executive calendars, coordinating meetings and travel, and overseeing daily office operations in a fast-paced environment.

Develop and test AI-powered software solutions, collaborating with team members and learning about AI tools and frameworks.