Principal Outbound Product Manager - AI / Agentic Automation

Job description

BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world’s largest organizations so they can seize a competitive advantage. Enterprises need more than impressive AI demonstrations. They need automation that works within real operating environments, respects controls and delivers measurable business results. As Principal Outbound Product Manager, AI and Agentic Automation, you will turn customer needs and technical capabilities into a clear market strategy and repeatable adoption for BMC’s Digital Business Automation portfolio. Your focus will span AI capabilities for Control-M and new agentic AI products, exploring opportunities both to improve workflow creation and operations and to orchestrate AI-enabled work. Control-M orchestrates application and data workflows across mainframe, on-premises and cloud environments. In this principal individual-contributor role, you will own outbound strategy for assigned AI offers and connect their value to the broader portfolio narrative. You will partner with inbound product management, AI engineering, solution marketing, sales and presales, forward-deployed engineering and solutions teams, customer success, partners and security. Inbound product management and engineering retain roadmap and implementation decisions; you bring market evidence and drive commercial readiness and adoption. Here is how, through this role, you will contribute to BMC’s and your own success: Define target segments, buyer and user personas, and priority use cases for assigned AI offers across the portfolio. Build value hypotheses and business cases with customers, using agreed baselines for time-to-value, productivity, operating cost and quality. Own differentiated positioning and competitive insight for assigned AI offers, in partnership with solution marketing. Explain what the product can do today, its maturity, deployment requirements and limits, without promising capabilities or autonomous reliability that have not been demonstrated. Lead launch and market-readiness plans with product and cross-functional teams. Align the use-case story, launch criteria, reference architectures, demonstration paths, seller assets and customer-success preparation so a launch can support real adoption. Build and validate compelling demonstrations with architects and AI engineering. Equip sellers, presales, solutions teams and partners with practical discovery guides, objection handling and hands-on training that connect technical behavior to business value. Recruit and support design partners and early-access customers. Define pilot entry and exit criteria, evaluation methods, business baselines and production-readiness gates with product, engineering and customer teams; turn results into credible customer evidence. Drive the path from pilot to production with customer success and delivery teams. Identify barriers to activation, integration and sustained usage, and build repeatable adoption playbooks rather than treating a successful demo as the finish line. Make trust and control part of the value story. Work with engineering and security to explain permissions, grounding, evaluation and failure modes, human approvals, governance and auditability, and help customers understand where oversight is essential. Support strategic customers and sales opportunities through discovery, executive discussions and solution validation. Represent assigned offers with analysts, partners and at industry events, drawing on evidence and real customer needs. Translate customer, field, competitive and usage insights into clear recommendations for inbound product management. Influence priorities with evidence while keeping roadmap and implementation ownership with product management and engineering. Provide market and customer input into packaging, pricing and commercialization. Where consumption-based models are relevant, test the economics of usage, quality, cost and customer value instead of assuming that more consumption means more benefit. Measure adoption and field readiness, share learning across the portfolio and mentor peers. Help teams make sound decisions across functions without relying on reporting-line authority. To ensure you’re set up for success, you will bring the following skillset & experience: 10+ years in enterprise software across product management, outbound product management, technical product marketing, presales or solutions roles, with a strong launch record and substantial direct customer experience. Demonstrated ownership of an externally sold enterprise AI or agentic offering beyond demonstrations, through customer pilots to measured production adoption. You can explain your contribution, the decisions you made and the evidence of customer value. Credible hands-on familiarity with large language models, retrieval and grounding, tool use and agent workflows. You can validate a demonstration or prototype, work closely with architects and explain quality, cost, latency and trust tradeoffs to technical and executive buyers. Strong positioning and communication skills, with a record of turning complex technology into clear customer outcomes, effective field enablement and persuasive executive conversations. Ability to design customer validation, distinguish promising experiments from production evidence and build ROI cases from agreed baselines rather than unsupported projections. A record of influencing engineering, marketing, sales and customer-success teams, exercising sound judgment in ambiguous markets and taking initiatives from strategy through execution. A degree in a relevant field or equivalent practical experience. Whilst these are nice to have, our team can help you develop in the following skills: Experience with application or data workflow orchestration, enterprise automation platforms and hybrid environments spanning mainframe, on-premises and cloud. Experience integrating enterprise AI or agent ecosystems, particularly where permissions, governance, operational controls and auditability matter in regulated deployments. Familiarity with SaaS commercialization and usage economics, and the ability to explore an AI platform or validate a lightweight prototype using APIs or Python. What success looks like In your first year, success will show in the market-readiness outputs you own and the customer and commercial outcomes you shape with partner teams. Repeatable target use cases and segments, supported by validated customer needs, agreed business baselines and a differentiated story for assigned AI offers. Credible customer proof from design partners and pilots, with clear success criteria, honest evaluation findings and practical playbooks for moving into production. Market-ready launches with accurate demonstrations, agreed readiness criteria and trained sellers, presales and partners who can qualify opportunities and explain both value and limits. With sales and customer success, progress from pilots to activation and sustained production usage, measured against agreed customer baselines for time-to-value, business benefit and AI quality. Pipeline influence and commercial results are shared outcomes, distinct from your direct readiness and enablement commitments. CA-DNP Our commitment to you! BMC’s culture is built around its people. We have 6000+ brilliant minds working together across the globe. You won’t be known just by your employee number, but for your true authentic self. BMC lets you be YOU! If after reading the above, You’re unsure if you meet the qualifications of this role but are deeply excited about BMC and this team, we still encourage you to apply! We want to attract talents from diverse backgrounds and experience to ensure we face