[Hiring] AI/ML Presales Solutions Architect @Marlabs

Role Description

As an AI/ML Presales Solutions Architect, you are the technical authority supporting client conversations early in the sales cycle. You are responsible for understanding client problems, determining the right AI/ML approach, and shaping feasible, valuable solutions that align with both client needs and delivery capabilities. You thrive in exploratory, client‑facing environments where discovery, judgement, and solution framing matter more than hands‑on model building. You partner closely with sales to accelerate opportunities while ensuring we never over‑commit beyond what can realistically be delivered. You bring broad knowledge across AI, data platforms, and cloud ecosystems and are comfortable explaining what is possible, what is not, and the tradeoffs between different approaches.

Qualifications

• 10+ years of experience spanning AI/ML, data platforms, cloud architecture, or advanced analytics, with strong client‑facing exposure.
• Proven experience in sales engineering, presales solutioning, or technical consulting roles supporting enterprise clients.
• Broad knowledge of AI/ML use cases and architectures, with the ability to evaluate solutions across platforms such as Databricks, Snowflake, Azure, Salesforce, and related ecosystems.
• Strong ability to conduct solution discovery, assess feasibility, identify risks, and articulate architectural tradeoffs.
• Experience creating client‑facing presentations, architecture diagrams, and solution narratives that support sales cycles.
• Comfortable working at the intersection of sales, delivery, and technical leadership, knowing when to escalate or pull in additional expertise.
• Excellent communication skills with the ability to explain complex AI concepts to both technical and non‑technical stakeholders.

Requirements

• Act as the primary technical presales partner, supporting multiple client engagements across discovery, solution design, and capability discussions.
• Lead early client conversations to understand business problems and determine the fastest, most effective path to an AI/ML solution using preferred client technologies.
• Translate open‑ended client challenges, such as model drift, OCR alternatives, AI automation needs, into clear solution approaches, architecture options, and recommendations.
• Define solution architecture, tradeoffs, timelines, and required resources, pulling in delivery teams or subject‑matter experts only when needed.
• Guide the AI Lab and technical teams by synthesizing client discovery into clear direction for demos, proofs of concept, and presentations.
• Create client‑facing materials, including slide decks, architecture diagrams, solution flows, implementation approach, and discovery plans.
• Partner with sales leadership on estimations, pricing inputs, and scope definition, ensuring alignment between proposed solutions and delivery feasibility.
• Stay current on emerging AI tools, platforms, and market trends, continuously evaluating how new capabilities integrate into existing ecosystems.