Top Tech Jobs & Startup Jobs

Lead strategic engagement for enterprise SaaS customers to drive adoption, retention, renewals, and expansion. Build executive and technical relationships, create account plans, monitor health and usage, coordinate cross-functional teams, and deliver measurable outcomes in software quality and engineering efficiency.

Lead and mentor teams in developing language model-based AI solutions, ensuring high technical standards, quality implementations, and effective communication with stakeholders.

The Legal Counsel will provide legal advice and support for commercial transactions, assist in corporate transactions, and develop company policies and procedures in compliance with legal standards.

Drive growth through strategic partnerships with Deloitte, managing joint solutions and marketing initiatives while engaging cross-functional teams to achieve business objectives.

As a Senior Technical Consultant, you will develop custom solutions for Tricentis products, manage client relationships, mentor junior consultants, and provide documentation and reporting for multiple projects.

The Vice President will lead data-driven decision-making in GTM, overseeing analytics transformation and aligning C-suite stakeholders on performance metrics and insights.

Sell continuous testing software, engage and educate customers, and collaborate with a team to enhance customer outcomes in a rapidly-growing startup environment.

Lead product marketing for AI and quality engineering offerings: develop persona-based positioning, create content across the sales lifecycle, support demand generation, conduct market and competitive research, influence product roadmap, run win/loss analysis, and represent the company externally to drive pipeline and adoption.

Lead engineering vision and architecture for LLM-based systems, mentor engineers, define org-wide standards for quality, safety, and observability, drive multi-team production initiatives, own platform and cloud-native decisions, and resolve high-severity AI production incidents.

Design and evolve a scalable, secure AI platform and reference architecture. Lead model selection, RAG/agent frameworks, vector DBs, feature stores, MLOps, inference optimization, and governance. Provide architectural direction for agentic AI, LLMOps/AIOps, observability, and responsible AI. Influence engineering teams and cross-functional stakeholders to implement production-grade AI systems.