AI Go To Market Leader

Verizon•Temple Terrace, FL

2d•Hybrid

About The Position

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What you’ll be doing... As the Associate Director of Systems Architecture for Revenue Operations, you will be the primary architect and "AI Copilot" for our GTM engine. You will lead a specialized team of contracted engineers to move beyond basic analytics and build agentic workflows and RAG systems that directly supercharge our sales and marketing teams. This is a high-impact, hybrid role requiring a "hacker" mindset to rapidly prototype AI-native tools that eliminate friction in the sales journey. You will be working to architect and deploy Generative AI solutions that eliminate friction in our Go-To-Market (GTM) engine. You will move beyond traditional data analytics and modeling to design and build agentic workflows and RAG (Retrieval-Augmented Generation) systems that drive a create intuitive, AI-native employee experience to our GTM representatives that supercharge our sales and marketing teams.

Requirements

The AWS Stack & Infrastructure Infrastructure as Code (IaC): Deep expertise in AWS CloudFormation/CDK to ensure all virtual services are secure, version-controlled, and auditable
AI & Orchestration: Expertise in AWS Bedrock, Bedrock AgentCore, Strands
Environment & Security: Familiarity with AWS IAM, VPC, and networking infrastructure to maintain a "security-first" architecture
Data Foundation: Experience with AWS S3, Redshift, and Aurora as the backbone for AI-powered solutions.
AI-Native Software Engineering skills Python (Programming Language): Advanced proficiency to guide AI agents and ensure the technical foundation is robust
Agile Methodology: Lead the team through iterative development cycles, driving continuous improvement and continuous integration (CICD) in AI/ML workflows
Agent-assisted coding: familiarity with a responsible use of code assistance tool such as Claude Code, AWS Kiro or Github Copilot
Experience with Lambdas, Step Functions, API gateways and serverless solutions
Management & Leadership Skills A product-oriented and revenue-focused mindset: the ability to deeply empathize with a representative's workflow and design AI outputs that are instantly actionable during a live call.
Evangelist Energy: You are genuinely excited about AI. You follow the latest releases, read the relevant papers, and can explain why "reasoning models" matter to a non-technical sales or customer success stakeholder.
Methodology : You must possess an 'Agile-for-GTM' approach: prioritizing the rapid feedback loops of a sales cycle over rigid, long-term development sprints. We need someone who can use Agile ceremonies to manage the inherent uncertainty of AI outputs while maintaining a high-velocity deployment schedule.
Tooling: Expert-level proficiency in Agile project management tools (e.g., Jira, Azure DevOps, or Linear) to track experimentation as well as production tasks as well as standard software development tools (Git, Docker) and CI/CD processes.

Nice To Haves

Domain expertise in Go-To-Market, RevOps, or Sales tech stacks (Salesforce, Amazon Connect, Gong, Salesloft, Marketo, Gainsight).
Experience building real-time audio/speech-to-text processing pipelines (e.g., Amazon Connect/Kinesis, WebRTC, Deepgram, Whisper) for live transcription and analysis.
Familiarity with the LangChain platform and ecosystem
Experience with AI evaluation and observability tools
Knowledge of "agentic" design patterns

Responsibilities

Architectural Design, Strategy & Mentorship Blueprinting: Design large-scale AI solutions, their architecture and the integration with modern enterprise cloud ecosystems
Discovery: Exploring and eliminating other GTM friction points by rapid prototyping AI solutions for lead enrichment, personalized outreach, and CRM automation.
Technical Strategy: Drive the strategy of the AI engineering technical team and manage its execution, keeping up to speed with the latest industry knowledge and methods for AI/ML
Mentorship: Provide support and guidance to teammates, fostering a culture of technical excellence and sharing advanced AI methodologies
Responsible AI: Drive the standards and principles that ensure all AI processes are transparent and secure, contributing to the definition of KPIs and auditory requirements
AI Evangelism & Enablement: Act as the "AI Copilot" for the revenue and GTM teams. Run internal workshops, drive EnGRAM approvals, create Gemini Gems and agent instruction files, and teach the broader GTM org how to leverage AI tools to 10x their speed and conversion rates.
AI-Native Engineering & Execution Value-Driven Deployment: Own the whole lifecycle of the AI-powered solutions, from build to deployment to performance and cost monitoring
System Optimization: Constantly review and refine system performance for scalability and cost effectiveness
Developing and maintaining production-grade infrastructure for AI orchestration, including prompt management, low-latency streaming APIs, and model evaluation frameworks.
Drive Rapid "Vibe Coding" & Prototyping: Use tools like Claude Code, Codex, Lovable, LangSmith Agent Builder, to go from idea to deployed full-stack MVP in days, not weeks.