About rapid canvas rapid canvas 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. Rapid canvas 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. Rapid canvas 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.
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 rapid canvas can build and what customers actually need.
what you’ll own
pre‑sales
* 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 rapid canvas 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
* 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, rapid canvas 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
* 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 stand‑ups, track task progress across rapid canvas 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 customer experience.
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. Your academic, professional, and personal experiences should demonstrate strong ownership, execution, and customer‑facing instincts.
must‑have
* 3–8 years of experience in client‑facing roles with a delivery or technical component— 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—ability to hold credible conversations about ai/ml concepts: llms, gen ai, rag, fine‑tuning, model evaluation; data engineering: pipelines, etl/elt, data quality, apis, databases; 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.).
* hub spot, jira, or confluence experience.
* background in enterprise software, saas, or data platforms.
* experience with general or cross‑cultural client engagements.
* familiarity with ai concepts like gen ai, llms, rag, or automation workflows.
* experience in enterprise environments or global customers.
why join rapid canvas
this role shapes the future of enterprise ai—leading real, production‑grade agentic ai deployments for global enterprises. You’ll accelerate your career by learning from a leadership team with 15+ years of ai experience and 6 ipos behind them. Your work directly impacts revenue, customer retention, and the growth of an ai platform recognized in the top5 on g2. We offer a high‑performance culture, competitive compensation and benefits tailored to your local market, and the chance to build the ai‑native enterprise of tomorrow.
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