Manager - Applied AI & GTM Systems - Confluent

Introduction At IBM Global Sales, we bring together innovation, collaboration, and expertise to help clients solve their most complex business challenges. Working across industries and geographies, you’ll partner with colleagues, clients, and partners to co-create solutions that drive digital transformation and lasting impact. Success in Global Sales is built on curiosity, empathy, and collaboration. You’ll connect technical understanding with strong people skills, building trusted relationships and shaping solutions that improve business and society. With world‑class onboarding, continuous learning, and a supportive culture, IBM offers the tools and opportunities to grow your career. Join us and be part of a global team that’s passionate about driving innovation and making a difference. Your role and responsibilities This is a GTM engineering role where business context matters as much as technical execution. You’ll take real workflow pain from the field — pipeline generation, deal execution, sales operations, adoption, expansion, renewal — and translate it into practical, measurable improvements using AI agents, automation, and better data flow across systems. That means you need to understand how revenue teams actually work, where deals stall, why handoffs break, and what "good" looks like before you build anything. You’ll expand the agent portfolio, harden what’s already live, and push into new use cases across the customer lifecycle. You’ll influence GTM AI strategy by shipping what works, setting a high bar for quality and operational rigor, and creating reusable patterns that scale. You’ll own outcomes end‑to‑end: turning ambiguous asks into a clear plan, making tradeoffs quickly, and shipping measurable improvements on a steady cadence. You’ll act as the internal GTM AI SME, promoting responsible AI adoption and automation across GTM teams by recommending effective patterns, tooling, and best practices. What You Will Do Own AI intake and delivery across Sales and CSG: run intake, clarify business problems, define requirements and success metrics, prioritize the backlog, and drive new initiatives from 0 to 1 while iterating on the 100+ agents already in production. Build and ship AI workflows end‑to‑end: Expand the existing agent portfolio into new use cases while hardening and improving what’s already live. Map current‑state processes, identify friction, design future‑state workflows, and implement agents and automations that teams can rely on day to day. Translate GTM context into technical decisions: Understand pipeline mechanics, sales motions, CS health models, and renewal workflows well enough to know which problems are worth solving and which solutions will actually get adopted. Partner cross‑functionally to unblock delivery: work day‑to‑day with Sales, Customer Success, Marketing Ops, Business Technology, Data Science, Finance, and Legal to align on requirements, data usage, governance, and measurable outcomes. Launch what you build: drive rollout with lightweight enablement (training assets, office hours, comms), gather feedback, and continuously improve workflows after release. Own quality and operational rigor: create test plans, run QA, manage prompt and workflow versioning, and maintain documentation, runbooks, and release notes so delivery is safe and repeatable. Measure impact and iterate: track adoption and performance, validate results in partnership with Ops and Analytics, and continuously improve workflows based on usage and outcomes. Required technical and professional expertise 3 to 5+ years in Revenue Operations, GTM Systems, Sales Ops, CS Ops, Business Systems, or similar roles improving GTM execution through process, systems, and automation. A pattern of taking ambiguous GTM problems, getting to the root cause fast, and shipping improvements that teams actually adopt. Business acumen that shapes what you build. You understand how pipeline is generated, how deals move, how CS teams manage renewals and expansion — and you use that context to prioritize the right problems and design solutions reps and CSMs will actually use. Strong judgment and follow‑through: you surface tradeoffs early, close open loops, and keep work moving from idea to rollout to iteration. Comfort with the technical basics that power modern GTM automation, including APIs/webhooks, JSON payloads, and SQL for validation or analysis (BigQuery preferred). Salesforce fluency and comfort working across pipeline, lifecycle, and post‑sales workflows. Preferred technical and professional experience Hands‑on experience with Claude Code or similar AI‑native development tools. You’ve used LLMs not just as a feature you’re configuring but as a tool you build with — generating code, iterating on prompts, scaffolding automations, and shipping faster because of it. Familiarity with GTM Systems like Relevance AI, Momentum, Clay, Salesloft, Zoominfo, Clari, D&B, DemandTools, 6sense, Highspot, Loopio. Experience building AI workflows with governance patterns (access controls, auditability, feedback loops). IBM is committed to creating a diverse environment and is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status. #J-18808-Ljbffr IBM Computing