BforeAI

Sales Operations Manager

• Build and launch BforeAI's sales education program from onboarding through ongoing development
• Define the knowledge and skills required for Account Executives and Sales Engineers to win opportunities
• Create and maintain sales scripts and supporting materials
• Analyze sales motions, wins, losses, opportunities, pitches, and objections to improve performance
• Join customer presentations and feed recurring challenges back into training and messaging
• Create and present playbooks for products and target verticals, including pitches, demos, value propositions, and objection handling
• Partner with Product and product experts to translate technical capabilities into sales messaging
• Build opportunity scenarios, run role-plays, grade participants, and create improvement plans
• Track Account Executive and Sales Engineer performance for targeted enablement
• Report individual and team product-messaging capability to leadership
• Support customer calls alongside Account Executives and Sales Engineers
• Create public-facing content including blogs, LinkedIn posts, white papers, and SEO content
• Represent BforeAI as a technology expert at webinars, industry events, and outreach opportunities

VP Sales Enablement

Data Engineer

• Design, implement, test, deploy, and operate production services for ingestion, normalization, enrichment, identity resolution, scoring, and intelligence delivery
• Build maintainable pipeline workers, event consumers, APIs, scheduled processes, and supporting libraries
• Own the complete software lifecycle, including architecture, implementation, testing, deployment, monitoring, incident response, and improvement
• Establish reusable engineering patterns for the team
• Develop asynchronous workflows with explicit data, event, and work contracts
• Design for duplicate delivery, ordering constraints, idempotency, retries, timeouts, partial failure, dead-letter handling, backpressure, and recovery
• Make pipeline state and failures observable, with reconciliation for missing, delayed, duplicated, or inconsistent processing
• Support safe replay and reprocessing without silently changing historical-result meaning
• Preserve source evidence, provenance, lineage, processing context, and applicable versions
• Define validation and quality controls at service boundaries and safely evolve schemas, contracts, and processing logic
• Preserve tenant isolation while combining shared intelligence with customer-private evidence, configuration, and conclusions
• Apply authorization, retention, deletion, audit, GDPR, and SOC 2 requirements throughout data-processing workflows
• Evaluate managed services, open-source components, existing capabilities, and purpose-built services based on product and operational requirements
• Contribute to architecture through working software, written proposals, prototypes, and technical review
• Collaborate with Product, Platform Engineering, Threat Research, Data Science, Security, and customer-facing teams
• Translate product requirements into technical contracts, communicate tradeoffs, and mentor engineers in modern data and distributed-systems practices

Senior Data Engineer, Product Data Systems

• Design, implement, test, deploy, and operate production services for ingestion, normalization, enrichment, identity resolution, scoring, and intelligence delivery
• Build maintainable pipeline workers, event consumers, APIs, scheduled processes, and supporting libraries
• Own the complete software lifecycle, including architecture, implementation, testing, deployment, monitoring, incident response, and improvement
• Establish reusable engineering patterns for the team
• Develop asynchronous workflows with explicit data, event, and work contracts
• Design for duplicate delivery, ordering constraints, idempotency, retries, timeouts, partial failure, dead-letter handling, backpressure, and recovery
• Make pipeline state and failures observable, with reconciliation for missing, delayed, duplicated, or inconsistent processing
• Support safe replay and reprocessing
• Preserve source evidence, provenance, lineage, processing context, and applicable versions
• Define validation and quality controls at service boundaries and safely evolve schemas, contracts, and processing logic
• Preserve tenant isolation while combining shared intelligence with customer-private evidence, configuration, and conclusions
• Apply authorization, retention, deletion, audit, GDPR, and SOC 2 requirements
• Evaluate managed services, open-source components, existing capabilities, and purpose-built services
• Contribute to architecture through working software, proposals, prototypes, and technical review
• Collaborate with Product, Platform Engineering, Threat Research, Data Science, Security, and customer-facing teams
• Translate product requirements into technical contracts, communicate tradeoffs, and mentor engineers