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Engageware

Senior Product Manager – AI Suite

Posted 12 Days Ago
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Remote
Hiring Remotely in México
Senior level
Remote
Hiring Remotely in México
Senior level
Own the end-to-end lifecycle and roadmap for an enterprise AI suite spanning voice, live agent, conversational AI, automation, and personalization. Lead customer discovery, AI/ML and engineering collaboration, integrations with contact center and CRM ecosystems, agile delivery, metrics-driven iteration, go-to-market readiness, and post-launch optimization. Partner with customers and cross-functional teams across the Americas, support regulated-industry requirements, mentor junior PMs, and drive adoption, retention, and growth.
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Why You’ll Love This Role

We’re seeking a forward-thinking Senior Product Manager to help lead the next generation of our AI suite, including our voice and live agent capabilities. Based in Mexico and partnering closely with engineering teams and enterprise customers across the Americas, you’ll own the full product lifecycle, from discovery through delivery, adoption, and iteration. You’ll drive the roadmap, collaborate cross-functionally, and build experiences that help our regulated enterprise customers scale engagement, improve service, and grow with confidence. This role combines senior product leadership with the exciting challenge of leveraging AI to solve real problems for customers in banking, credit unions, wealth management, insurance, and telecom.

Your Responsibilities

  • Innovation through Customer Insight
    Engage directly with enterprise customers across the Americas through discovery interviews, advisory boards, and QBRs to uncover unmet needs and validate new ideas. Translate pain points into opportunities where conversational AI, automation, or personalization can drive breakthrough value.
  • AI-Driven Product Strategy
    Collaborate on the vision and roadmap for our AI suite, including voice and live agent experiences, with a strong emphasis on embedding agentic and conversational capabilities. Partner with AI/ML and engineering teams to identify use cases such as agentic orchestration, voice automation, agent assist and co-pilot, smart routing, and conversational analytics. Evaluate build-vs-buy decisions and ensure technical feasibility, including the accuracy, governance, and compliance controls regulated customers require.
  • Channel + Ecosystem Integration
    Lead product thinking around integrations with contact center (CCaaS), CRM, messaging, telephony, and other core systems to ensure customer context and knowledge are actionable and seamlessly integrated into customer conversations and workflows.
  • Execution & Delivery
    Translate strategic goals into PRDs, epics, and user stories. Partner with engineering throughout the development lifecycle (sprint planning, backlog grooming, and release management) to deliver features that drive customer growth and retention. Collaborate with UX, product marketing, and sales enablement to ship products that add measurable value to enterprise customers. Ensure roadmap priorities are aligned with our key ICPs and target the most important product gaps based on competitive and market landscape.
  • Metrics-Driven Iteration
    Define and track KPIs that reflect product success across the full lifecycle. Analyze adoption, retention, and usage patterns to refine experiences post-launch and inform prioritization decisions.
  • Go-to-Market Readiness
    Lead cross-functional Go To Market activities for new launches and upgrades. Collaborate with product marketing, sales, and customer success to position our AI suite as a differentiator. Create enablement materials and ensure internal teams and enterprise clients can adopt and trust your product.
  • Product Lifecycle Ownership
    Own the end-to-end product lifecycle from ideation through development, launch, post-launch optimization, and end-of-life. Ensure each phase has clear success criteria and customer feedback loops. Drive continuous improvement through retrospectives and lessons learned.
  • Cross-Border Enterprise Collaboration

         Work effectively across time zones with engineering, sales, customer success, and executive teams in the US             and Latin America. Serve as the product voice in customer-facing meetings and executive reviews. Mentor                   junior product team members and help build PM best practices across the organization.

Your Qualifications

  • 7+ years in B2B SaaS product management, with experience owning products serving enterprise customers; conversational AI, contact center, or customer engagement platform experience is a strong plus
  • Working knowledge of AI and LLM concepts (such as RAG, agentic workflows, and evaluation) and how they apply to customer-facing products
  • Strong understanding of customer experience design and product usability
  • Skilled at turning complex technical solutions into intuitive user experiences
  • Hands-on experience owning the full product lifecycle from concept through launch, adoption, iteration, and end-of-life
  • Demonstrated experience working with enterprise SaaS companies and customers across the Americas, including direct customer engagement and cross-time zone collaboration
  • Fluency in both English and Spanish, written and verbal (business-fluent or native-level in each), to engage customers and teams across the Americas
  • Willing to travel to the US and Latin America for business meetings and customer visits as needed (15-20%)
  • Excellent communication and presentation skills across technical and non-technical audiences
  • Ability to develop a business strategy, create a product vision, and craft a roadmap to achieve business goals
  • Experience working embedded with engineering teams in agile environments (sprint planning, backlog management, trade-off discussions)

Preferred Experience

  • Prior experience in banking, credit unions, wealth management, insurance, or telecom (regulated industries)
  • Experience with conversational AI, virtual assistant, or contact center (CCaaS) platforms such as Genesys, NICE, or Twilio.
  • Experience with voice AI technologies (speech-to-text, text-to-speech, telephony/SIP).
  • Knowledge at a configuration or administrative level of messaging and omnichannel channels such as WhatsApp, RCS, SMS, and web chat, and/or of CRM and knowledge management systems.
  • Technical background (engineering, data science, or analytics)
  • Success working with AI/ML teams to bring predictive, automated, or generative (LLM, RAG, agentic) features to market

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