Top Tech Jobs & Startup Jobs in Birmingham, AL

Provide empathetic financial guidance to participants, addressing financial challenges, delivering support, and creating educational content while working independently.

The Technical Support Engineer resolves customer support tickets, diagnoses technical issues related to email delivery, onboarding, and integrations, and escalates bugs while documenting solutions.

The Solutions Architect will manage technical relationships, design demos, oversee onboarding, and translate customer needs into product insights, while working with sales and engineering teams.

The Founding Product Manager will lead the development of AI-driven surgical data products, translating user needs into product requirements and managing the product lifecycle from ideation to deployment.

The EHSS & Quality Senior Analyst leads data management for EHS, ESG, and Quality goals, ensuring compliance and driving continuous improvement initiatives. Responsibilities include data collection, analysis, and reporting, as well as the development of dashboards and automation processes.

The Systems Engineer on Database Administration will support database installations, optimization, maintenance, and work with teams to enhance query performance.

The Project Manager oversees client orders, ensuring timely fulfillment and satisfaction while driving operational efficiency and managing vendor relationships for promotional and print projects.

The Key Account Manager will manage key accounts in the Casino Gaming industry, drive sales growth, and collaborate with technical teams. Responsibilities include developing customer strategies, building sales pipelines, and establishing partnerships.

As a Customer Success Manager at Nevis, you'll enhance client relations, drive product engagement, collect feedback for product development, and support Registered Investment Advisors in using Nevis's AI platform effectively.

As a Founding Software Engineer, you'll architect and evolve core backend systems and streaming data pipelines, optimize performance and storage, and define data models to enhance AI deployment safety and performance in real-time environments.