Enterprise Sales Lead, AI Data Operations

Arise

Enterprise Sales Lead specializing in AI Data Operations and enterprise deals. Building pipeline and delivering technical solutions in a rapidly evolving AI ecosystem.

Posted 7/29/2026full-timeRemote • California • 🇮🇳 India, 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in enterprise sales and business development within the AI ecosystem, with a strong focus on the AI data lifecycle, operational complexity, and consultative communication. Proven ability to generate pipeline and close deals while collaborating with technical teams and senior leadership.

Highest-signal resume keywords

Enterprise Sales ExperienceAI Data Lifecycle FluencyPipeline GenerationAnnotation Platform FamiliarityConsultative Communication

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data CollectionData AnnotationQuality AssuranceModel EvaluationSales StrategyNegotiationTechnical ScopingOperational Complexity

Soft Skills

Excellent CommunicationConsultative Instincts

Tools & Technologies

LabelboxScaleEncordArgillaAWSGCPAzure

Industry Keywords

AI EcosystemConversational AIVoice/ASRApplied ResearchCXContact Center Data

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Own pipeline generation. This is a build role, not an inherited-book role.
You will be feet on the street in the Bay Area, working the AI ecosystem directly — labs, applied ML teams, AI platform companies, and enterprise automation buyers.
Sell the technical work, not the logo.
Data collection and annotation, human-in-the-loop QA, preference and ranking data, model evaluation and red-teaming, conversational and multimodal datasets, agent-trajectory data.
Scope with the people who deliver it.
You will work directly with operations and AI engineering to build programs that are actually deliverable — throughput, quality thresholds, ramp plans, and pricing that survives contact with a real workload.
Partner with senior leadership on presentations, proposals, and negotiations for enterprise deals.
Feed the roadmap. You are closest to what buyers are asking for next. We want that intelligence coming back into service design.

Requirements

What you’ll need

5–7+ years in enterprise sales, business development, or account management, with meaningful time in technology or AI services
Working fluency in the AI data lifecycle — collection, labeling, QA, evaluation — enough to hold your own in a technical scoping call without a solutions engineer in the room
A track record of self-generated pipeline and closed net-new logos
Comfort selling a services motion with real operational complexity behind it
Excellent written and verbal communication; genuinely consultative instincts
Familiarity with annotation platforms (Labelbox, Scale, Encord, Argilla) and cloud ecosystems (AWS, GCP, Azure)
Background in CX, contact center data, conversational AI, or voice/ASR
Experience selling into frontier labs or applied research teams
Experience working across globally distributed delivery teams

Benefits

Comp & perks

Fully remote company, with real infrastructure for distributed work across six countries