Enterprise Sales Development Representative

About the role

This position places you as an in-person Enterprise Sales Development Representative in San Francisco, working at the forefront of enterprise AI customer experiences. You will directly represent the company by initiating outbound activity alongside elite Account Executives to build a robust pipeline. Every qualified conversation you start will influence how large consumer brands implement and deploy AI-powered support and operations solutions. The role operates within fast-paced, enterprise-focused workflows that demand consistent execution and rapid adaptation. You will receive structured coaching from leadership to refine your approach and sharpen your results over time. Your efforts will translate into tangible pipeline that supports joint wins with your enterprise-facing partners. This is a hands-on role where your initiative directly shapes the company's enterprise growth trajectory.

Key facts

What you'll do

Daily phone work prioritizes confident outreach to decision-makers to build a consistent pipeline.

Precise qualification identifies pain points and aligns value to set high-quality meetings with Account Executives.

Partnership with Account Executives refines strategy, messaging, and account targeting to support joint wins.

Consistent performance meets and exceeds goals for qualified pipeline and meetings.

You will leverage data-driven insights to tailor messaging and prioritize accounts with the highest potential.

Discovery calls with VP- and C-level leaders will uncover strategic needs and map AI solutions to business outcomes.

You will manage a structured sales cadence across multiple tools to maintain momentum and visibility.

Regular reporting on activities and pipeline health will inform decisions and enable continuous improvement.

You will contribute feedback from the field to help shape product messaging and positioning for enterprise segments.

Your work will establish a repeatable process for converting early interest into scheduled executive conversations.

Requirements

The posting states a bachelor's degree requirement. 1+ years of SDR or BDR experience in B2B tech or SaaS.

A proven record of prospecting into enterprise accounts with $100K+ deals.

Confidence communicating on the phone and skill in receiving replies from VP- and C-level leaders.

A process-driven, coachable approach with an entrepreneurial ability to build your own motion.

A competitive, team-oriented mindset, ideally shaped by sports, teaching, finance, or other performance-driven backgrounds.

A relentlessly curious, growth-minded commitment to advancing your sales career.

Practical notes

This is an in-person role at the San Francisco HQ with catered lunch daily, a dinner stipend, a $150/month wellness benefit, 401(k), paid parental leave, commuter benefits, and medical, dental, and vision coverage. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

The role emphasizes fast learning, coaching, and rapid advancement within a growth-stage organization. Core tools typically include outreach platforms, CRM systems, and communication suites used for high-volume prospecting.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

About the company

• Voice AI startup Giga raises $61M Series A https://fortune.com/2025/11/05/voice-ai-giga-raise-61-million-customer-service-series-a/
• DoorDash and Giga Partnership https://www.linkedin.com