Top Tech Jobs & Startup Jobs in Tampa Bay, FL

Drive new restaurant partner acquisition through full sales cycle: prospecting, qualifying, and closing to meet quotas. Maintain pipeline, update Salesforce, collaborate with onboarding, marketing, and internal teams to ensure successful launches and partner relationships. Perform in-market activities and up to 25% travel.

The AML Compliance Associate supports customer onboarding and due diligence in compliance with AML regulations, ensuring accurate customer identification and monitoring.

The Finance Data Product Owner leads the direction for finance data products, manages product strategy, and ensures data governance in alignment with business needs and AI integration.

The Sales Associate III engages customers, provides styling advice, drives sales through storytelling, and maintains store operations, ensuring an excellent customer experience.

The role involves building AI-driven e-commerce systems, managing Shopify operations, integrating with NetSuite, and driving revenue through innovative marketing automation.

Lead DoD-focused account strategy and sales for Combatant Commands (COCOM/STRATCOM/TRANSCOM). Develop account plans, drive multi-year pipeline, negotiate contracts, navigate federal procurement vehicles, work with system integrators and partners, and position Cloudflare security and cloud networking solutions to meet mission objectives.

Design, build, and operate a signal-driven GTM pipeline that identifies high-intent accounts, automates enrichment and scoring, integrates CRM and marketing systems, runs programmatic growth experiments, aligns targeting with Sales/RevOps, and measures pipeline and ROI driven by automated plays and AI-enhanced workflows.

The Implementation Services Manager will drive customer onboarding and implementation projects, leveraging AI to solve business problems and improve user experiences.

Lead Support Readiness and Quality Intelligence for Global Customer Support. Build AI-native workflows, design onboarding/upskilling programs, run QA and model validation, translate insights into coaching and KPIs (AHT, CSAT, time-to-proficiency), and align learning and quality to business priorities while managing and developing multi-functional teams.

Lead and grow a team of 6-8 Product Specialist AEs to drive new product adoption and quarterly targets. Hire, onboard, coach, and enable reps; coordinate with Mainline AEs, Sales Engineers, and cross-functional pods (product, marketing, strategy) to optimize GTM, manage pipeline, create account plans, and execute high-value enterprise deals. Embed company culture and scale Specialist support globally.

Lead GTM data governance and strategy to improve Salesforce and GTM system data quality, ownership, and usability. Define KPIs linking data quality to pipeline/forecast accuracy, drive adoption of standards and scorecards, prioritize data improvements, lead cross-functional implementations, and build a team to scale revenue-impacting data practices.

Lead Apryse's Answer Engine Optimization and developer marketing: define AEO/GEO strategy, surface Apryse in LLM and AI search results, build developer community presence, produce technical content (code samples, integration guides), cultivate technical influencers, and align developer messaging with product and DevRel to drive pipeline and revenue.

Build and execute developer-focused AEO and off-page strategies across third-party developer channels. Create technical content (code snippets, guides, tutorials), engage authentically in developer communities, grow Apryse presence in LLM/AI answers, track pipeline attribution, and collaborate with product and content teams to align technical narratives with commercial outcomes.

Manage and grow a portfolio of large enterprise B2B SaaS customers across North America. Build executive relationships, develop account plans, drive expansion/up-sell, lead cross-functional teams, manage renewals, and ensure measurable business outcomes and retention.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.