Principal AI-First Product Manager

• Define a clear product strategy and roadmap that connects AMI Platform investments to customer outcomes and portfolio growth.
• Lead customer discovery with mainframe leaders, practitioners, and enterprise AI stakeholders; convert insights into validated problems, requirements, and differentiated product bets.
• Shape AI-native and agentic experiences, including assistants, specialized agents, coordinated workflows, tool use, knowledge grounding, and cross-domain orchestration.
• Partner closely with Engineering, Architecture, UX, AI Engineering, Data Science, Quality and Evaluation, Security, SRE, and portfolio product teams to make high-quality tradeoffs and deliver scalable platform capabilities.
• Own a portfolio of customer problems and use cases, prioritized by customer value, strategic differentiation, feasibility, reusable platform leverage, and business impact.
• Define measurable product success across user value, agent and task success, quality, trust, adoption, retention, latency, reliability, cost, and business impact.
• Set product requirements for evaluation, guardrails, governance, RBAC, audit, observability, explainability, and human-in-the-loop controls appropriate for enterprise and regulated environments.
• Drive 0-to-1 and MVP development with disciplined hypotheses, prototypes, design partners, and evidence-based decisions, then scale successful patterns across products and customers.
• Balance common platform capabilities with domain-specific needs, avoiding one-off solutions while creating practical paths to customer value.
• Develop business cases, competitive analysis, packaging recommendations, launch plans, field enablement, and adoption programs for new AI capabilities.
• Represent the product strategy with executives, customers, analysts, partners, Sales, and Customer Success, using clear and defensible narratives.
• Raise the bar for AI-first product management practices and mentor product managers through frameworks, coaching, and example.

• 8+ years of product-management experience in enterprise software, with evidence of setting strategy and delivering complex products across multiple teams or product areas.
• Demonstrated ownership of AI, generative AI, agentic AI, intelligent automation, AIOps, developer platforms, data platforms, or similarly complex technical products.
• Strong working knowledge of LLM-based systems, RAG and knowledge grounding, agents and tool use, orchestration, evaluation, observability, safety, and AI cost and performance tradeoffs.
• Previous background in a technical role, such as Architect, Software Developer, QA Engineer, Data Scientists or similar
• Understanding of how data quality, permissions, metadata, telemetry, and knowledge architecture affect AI product outcomes.
• Track record of translating ambiguous customer problems and emerging technologies into product strategy, roadmaps, requirements, and measurable outcomes.
• Experience taking 0-to-1 products or major capabilities from discovery through launch, adoption, and iteration.
• Excellent customer discovery, analytical, prioritization, and executive communication skills.
• Ability to influence Engineering, Architecture, UX, Security, GTM, and senior leaders without relying on formal authority.
• Strong commercial judgment, including business cases, market and competitive analysis, packaging, pricing inputs, and launch and adoption planning.
• Comfort operating in mission-critical enterprise environments where trust, security, deployment flexibility, and operational rigor matter.
• Bachelor's degree or equivalent practical experience in a relevant field.

• Experience with mainframe operations, observability, automation, database and data management, security, DevX, or enterprise infrastructure.
• Experience defining platform APIs, integration ecosystems, MCP-based capabilities, or extensible developer platforms.
• Knowledge of hybrid, on-premises, OpenShift, and cloud deployment models, including constraints in regulated or air-gapped environments.
• Experience with enterprise AI governance, responsible AI, model risk, compliance, or human-in-the-loop product design.
• Hands-on ability to prototype AI workflows using low-code tools, prompt and agent frameworks, APIs, or lightweight scripting.
• Experience working with design partners, analysts, strategic customers, and global go-to-market teams.

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 the world together with the best ideas!

BMC is committed to equal opportunity employment regardless of race, age, sex, creed, color, religion, citizenship status, sexual orientation, gender, gender expression, gender identity, national origin, disability, marital status, pregnancy, disabled veteran or status as a protected veteran. If you need a reasonable accommodation for any part of the application and hiring process, visit the accommodation request page.