Client Service Executive - Technology (Xico)

Overview

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. 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.

Role Summary

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 hybrid role combines client‑facing trusted advisor, technical solutions architect, and delivery lead responsibilities. You’ll work directly with senior executives and cross‑functional teams to ensure every engagement is technically credible, commercially sound, and operationally well‑run.

Responsibilities

Pre‑Sales Discovery

• 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.

Post‑Sales Project Scoping & 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 time‑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 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.
• Maintain high‑quality documentation and customer‑facing materials.
• Keep systems (Hub Spot, Slack, JIRA, Confluence, Drive) organized and up‑to‑date.

Industry Content & Strategic Value Support

• Develop tailored presentations highlighting AI use cases by vertical.

Qualifications

• Experience in engagement management, delivery management, or technical customer success.
• Management consulting experience 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—must hold credible conversations: data engineering (pipelines, ETL/ELT, data quality, APIs, databases), AI model deployment, and cloud platforms.
• 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.).
• Experience with Hub Spot, JIRA, or Confluence.
• Background in enterprise software, SaaS, or data platforms.
• Experience with global or cross‑cultural client engagements.
• Experience with enterprise environments or integral customers.
• Hands‑on experience working on real, production‑grade agentic AI deployments for global enterprises.

Compensation & Benefits

• Competitive compensation and benefits tailored to your local market.
• Recognized as a Top 5 Data Science and ML platform on G2 for customer satisfaction.

Why Join Us

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.