Our hybrid platform uniquely combines autonomous AI agents with human expertise, enabling organizations to deploy sophisticated AI applications without prohibitive costs or specialized technical teams.
Multi-agent systems will fundamentally transform how enterprises operate by autonomously executing complex processes that traditionally required extensive manual intervention—shifting organizations from labor-intensive workflows to intelligent, adaptive systems.
RapidCanvas disrupts the $5 trillion IT services market by replacing headcount-based billing and long implementation cycles with outcome-driven subscription pricing. Our customers deploy AI solutions 10x faster at 80% lower cost, while maintaining enterprise-grade quality, security, and measurable ROI.

We’re hiring a customer-facing AI Engagement Manager in LATAM to help drive and deliver enterprise AI projects end-to-end—spanning pre-sales discovery, technical solutioning, and post-sales execution through to value realization.
This is a hybrid role: part client-facing trusted advisor, part technical solutions architect, part delivery lead. You’ll work directly with senior executives and cross-functional teams to ensure every engagement is technically credible, commercially sound, and operationally well-run. You will act as a key driver of execution across the customer lifecycle—supporting solution definition, proposal creation, project coordination, and success tracking. Research, qualify, and follow up on enterprise prospects and new contacts
Prepare customer and industry research ahead of executive meetings, including relevant AI/ML use cases by vertical
Lead technical discovery conversations: understand data landscape, existing infrastructure, pain points, and readiness for AI adoption
Articulate how RapidCanvas works at a technical level — including our agentic AI architecture, data ingestion pipelines,



model orchestration, and deployment patterns —in a way that resonates with both technical and business stakeholders
Define and communicate realistic expectations around data engineering requirements: data availability, quality, volume, and preprocessing needs for each use case
Post-Sales: Project Scoping, Documentation & Customer Success Ownership
Lead the transition from sales to delivery by producing accurate, agreed-upon project scope documents — including technical requirements, data specifications, integration points, success criteria, and delivery milestones
Track milestones and outcomes across 30/60/90-day windows, surfacing risks and blockers proactively
Support UAT and rollout coordination to validate business outcomes and technical acceptance

AI Execution: Day-to-Day Project Leadership
Lead day-to-day project execution: run standups, track task progress across RapidCanvas and client teams, and maintain a clear delivery cadence
Understand and triage high-level technical issues — including bugs, data pipeline failures, model performance regressions, integration glitches, and deployment blockers — and coordinate resolution with engineering teams
Maintain high-quality documentation and customer-facing materials
Keep systems (HubSpot, Slack, JIRA, Confluence, Drive) organized and up-to-date
Industry Content & Strategic Value Support
Develop tailored presentations highlighting AI use cases by vertical




We’re looking for candidates who can walk into a boardroom and earn executive trust, then jump into a technical scoping session and hold their own with data engineers and ML teams. Engagement Management / Delivery Management
~ Technical Customer Success
~ Management Consulting with a technology focus
~ Demonstrated project management and execution ownership in fast-moving environments
~ Service-oriented mindset: you genuinely care about client outcomes and go the extra mile to ensure success
~ Technical fluency in AI, ML, and Data — you don’t need to be a developer, but you must be able to hold credible conversations about:
~ Data engineering: pipelines, ETL/ELT, data quality, APIs, database
~ Spanish fluency (written and verbal) — required for LATAM client engagements; English proficiency also expected for internal collaboration and documentation
~ Confidence and polish working with senior stakeholders: Familiarity with cloud platforms (AWS, GCP, Azure) or data tools (Snowflake, dbt, etc.)
HubSpot, JIRA, or Confluence experience
Background in enterprise software, SaaS, or data platforms
Experience with global or cross-cultural client engagements
HubSpot experience
Experience in enterprise environments or global customers

Work on real, production-grade agentic AI deployments for general enterprises — not internal tools or demos
High-performance culture that rewards execution, clarity, and accountability — not politics
Competitive compensation and benefits tailored to your local market
Recognized as a Top 5 Data Science and ML platform on G2 for customer satisfaction.

If you thrive at the intersection of business and technology, love owning complex projects end-to-end, and want to be part of building the AI-native enterprise of tomorrow — we want to meet you.

📌 Client Service Executive - Technology (Nezahualcóyotl)
🏢 RapidCanvas
📍 Nezahualcóyotl