This role involves leading strategic partnerships, enabling sales teams, and driving revenue growth through collaboration with various partners in the AI and enterprise software space.

The Account Executive will drive new business in customer experience solutions, manage lead generation, and build relationships with executives.

Join Ema as a founding SDR to build outbound sales, generate leads, qualify prospects, manage pipeline, and collaborate with teams.

The Account Executive will focus on lead generation, client engagement, pipeline management, deal closing, and market strategy to drive sales for AI solutions.

The role involves collaborating with sales and customers to architect technical solutions, manage customer integration, and promote Ema's AI platform.

Collaborate with sales teams to design and implement technical solutions, deliver product demonstrations, and assist customers from proof of concept to production.

The DevOps Engineering Lead will design and build infrastructure for a scaling product, manage deployments, automate tasks, and mentor junior engineers in a high-growth environment.

Design intuitive user experiences for enterprise applications, collaborating with teams and simplifying complex workflows through user-centered designs.

The Product Manager will define product strategy, conduct market research, manage product development, and collaborate with cross-functional teams to ensure successful product launches.

The Customer Success Specialist will enhance customer engagement, manage onboarding, drive product adoption, cultivate customer relationships, and address issues while tracking metrics.

The Enterprise Sales Executive will generate leads, engage clients, manage sales pipelines, negotiate deals, and strategize market approaches for AI solutions.

As an AI Application Engineer, you will customize GenAI applications, analyze customer data, deploy solutions at scale, and ensure integration and performance improvement, collaborating with teams and clients alike.

Assist senior ML engineers in researching, building, and deploying machine learning models, working with various data types while contributing to code reviews and technical discussions.