AI Engagement Manager

RapidCanvas transforms enterprises through AI by democratizing access to custom, enterprise-grade solutions. 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.

We believe agentic AI represents one of the defining enterprise opportunities of the next decade. 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.

RapidCanvas ranks as a Top 5 momentum leader among 250+ AI platforms, powered by leadership with 15+ years of AI experience from companies like Google. Our executive team has collectively contributed to 6 successful IPOs.

The Opportunity

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 be the bridge between what RapidCanvas can build and what customers actually need.

You will act as a key driver of execution across the customer lifecycle—supporting solution definition, proposal creation, project coordination, and success tracking. This is an ideal role for someone who thrives in fast-paced environments, loves owning details, and wants exposure to enterprise AI delivery at a high level.

What You’ll Own

Pre-Sales: Technical Discovery, Solutioning & Deal Progression

• 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
• Design, build, and deliver functional Proof of Concepts (POCs) and demos tailored to specific client use cases — not just slides, but working prototypes that demonstrate real AI value
• Co-Lead discovery workshops and whiteboarding sessions with client technical and business teams to map AI opportunities to business outcomes
• Develop and coordinate demos, and POC logistics (materials, agendas, environments, follow-ups)
• Draft and customize proposals, technical solution briefs, order forms, and client-facing deliverables

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
• Own Statement of Work (SOW) creation and stakeholder alignment: ensure all parties — client, RapidCanvas engineers, and leadership — share a clear and documented understanding of what will be built
• Drive clarity of scope, timeline, next steps, and ownership across stakeholders throughout the engagement lifecycle
• Lead structured check-ins with clear agendas, technical progress updates, notes, and action items
• Track milestones and outcomes across 30/60/90-day windows, surfacing risks and blockers proactively
• Ensure deliverables are packaged clearly and professionally for customers, including documentation, walkthroughs, and handover materials
• Support UAT and rollout coordination to validate business outcomes and technical acceptance

AI Execution: Day-to-Day Project Leadership

• Serve as the primary client point of contact throughout the delivery phase, providing consistent, professional, and technically informed communication
• 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
• Translate client-reported issues into clear, reproducible tickets for the technical team; communicate resolution timelines and workarounds back to the client
• Monitor progress against agreed technical milestones and proactively surface scope creep, dependency risks, or delivery gaps
• Participate in technical reviews and ensure the solution being built aligns with the original scoped requirements
• Contribute to continuous improvement: capture lessons learned, refine delivery templates, and improve the overall client experience

Operational Excellence

• Maintain high-quality documentation and customer-facing materials
• Keep systems (HubSpot, Slack, JIRA, Confluence, Drive) organized and up-to-date
• Ensure dashboards, pipeline reporting, and internal visibility are accurate
• Proactively surface blockers, risks, or unclear ownership with proposed solution

Industry Content & Strategic Value Support

• Develop tailored presentations highlighting AI use cases by vertical
• Create ROI models and phased AI roadmaps following workshops
• Help customers translate AI opportunities into business-ready plans
• Identify expansion opportunities based on usage, results, and evolving needs

Who You Are

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. We’re looking for candidates whose academic, professional, and personal experiences show strong ownership, execution, and customer-facing instincts.

Must-Have:

• 4–8 years of experience in customer-facing roles such as:
• Engagement Management / Delivery Management
• Technical Customer Success
• Solution Engineering or Pre-Sales Engineering
• Management Consulting with a technology focus
• Revenue / GTM Operations with technical depth
• 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:
• AI/ML concepts: LLMs, GenAI, RAG, fine-tuning, model evaluation
• Data engineering: pipelines, ETL/ELT, data quality, APIs, database
• Agentic systems: multi-agent orchestration, tool use, automation workflows
• Spanish fluency (written and verbal) — required for LATAM client engagements; English proficiency also expected for internal collaboration and documentation
• High attention to detail, accountability, and ownership of outcomes
• Confidence and polish working with senior stakeholders: VPs, GMs, CTOs, and Founders

Nice to have:

• Hands-on experience building demos, POCs, or prototypes (even in low-code/no-code environments)
• 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
• Familiarity with AI concepts like GenAI, LLMs, RAG, or automation workflows
• HubSpot experience
• Experience in enterprise environments or global customers

Why Join RapidCanvas

This isn’t a role where you manage status updates. This is where you shape the future of enterprise AI — and leave a visible mark on every customer you touch

• This isn’t a role where you manage status updates. This is where you shape the future of
• enterprise AI — and leave a visible mark on every customer you touch
• Be at the frontier: Work on real, production-grade agentic AI deployments for global enterprises — not internal tools or demos
• Accelerate your career: Learn enterprise AI selling and delivery directly from a leadership team with 15+ years of AI experience and 6 IPOs behind them
• Own real outcomes: Your work directly impacts revenue, customer retention, and the
• growth of an AI platform recognized in the Top 5 on G2.
• Grow fast: The AI market is moving at unprecedented speed — the skills you build here will define your career for the next decade
• Join a winning team: 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.