Sr. Sales Engineer (Forward Deployed Engineer - Pre Sales)

montecarlodata; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Fully remote position

Equity package

Job summary

montecarlodata is seeking a senior pre-sales engineer to enable large enterprise AI agent deployments at scale. You will own the technical win inside strategic US accounts, partnering with Account Executives to drive complex sales cycles from discovery through close.

You will focus on the emerging agentic stack—observability, reliability, and trust for production AI agents on modern data platforms—and translate customer data architectures into compelling ROI for executive buyers.

Qualifications

• Hands-on experience with enterprise AI and agent deployments.
• Fluency in AI observability concepts (traces, spans, evaluations) and instrumentation.
• 3+ years in pre-sales, solutions engineering or strategic technical account management at B2B AI-first or SaaS companies.
• Domain background in data, observability, agent trust, or agent-first products.
• Ability to whiteboard agent architecture with engineers and discuss ROI with senior leaders.
• Self-directed, accountable, and able to prioritize in a lean team.

Responsibilities

• Own end-to-end technical sales cycles including discovery, solution design, demos, proofs of value, and technical close.
• Help customers observe, trust, and improve AI agents deployed on enterprise data and AI platforms.
• Design and execute proofs of value with defined success criteria and deliver results to accelerate close.
• Develop technical champions through briefings, workshops, and reviews to position the platform as critical infrastructure.
• Incorporate customer data and AI architecture into account plans and quarterly business reviews.

Skills

Enterprise AI experience

AI observability

Solutions engineering

Pre-sales experience

Data observability

Technical storytelling

Self-directed

Tools

OpenTelemetry

Databricks Genie

Snowflake Cortex

Job description

Role overview

A senior pre-sales engineering role focused on helping large enterprise customers operationalize AI agent systems at scale. The position owns the technical win inside strategic US accounts, partnering directly with Account Executives to drive complex sales cycles from discovery through close. The work centers on the emerging agentic stack — observability, reliability, and trust for production AI agents running on modern data platforms.

Responsibilities

• Own end-to-end technical sales cycles including discovery, solution design, demos, proofs of value, and technical close within strategic enterprise accounts.
• Help customers evaluate how to observe, trust, and improve AI agents deployed on enterprise data and AI platforms — covering the data pipelines feeding agents, retrieved context, agent decisions, and outputs.
• Design and execute proofs of value with agreed success criteria, manage the evaluation, and deliver results that remove technical objections and accelerate commercial close.
• Identify and develop technical champions within each account through briefings, workshops, and architecture reviews that position the platform as critical infrastructure.
• Bring deep understanding of each customer's data and AI architecture — where agents run, how they are instrumented, and where reliability breaks down — into every account plan and quarterly business review.

Requirements

• Hands-on experience with enterprise AI and agent deployments, with real-world knowledge of architecture, failure modes, and the operational reality of moving agents from demo to production.
• Working fluency in AI observability concepts such as traces, spans, evaluations, and instrumentation; OpenTelemetry experience is highly valued, as is exposure to platforms like Databricks Genie or Snowflake Cortex.
• 3+ years in pre-sales, solutions engineering, or strategic technical account management at B2B AI-first or SaaS companies, with meaningful experience navigating procurement, infosec reviews, and multi-stakeholder buying committees inside large enterprises.
• Domain background in data, observability, agent trust, or agent-first products — having worked in the space, not adjacent to it.
• Ability to whiteboard an agent architecture with engineers while discussing ROI and competitive positioning with senior data and AI leaders; credible with engineers, effective with executives.
• Self-directed and accountable, comfortable prioritizing independently, knowing when to escalation, and knowing when to push back inside a lean team.

Nice to have

• Experience with the modern data stack (Snowflake, Databricks, dbt, Airflow, BigQuery, or similar) and background in data observability or data quality.
• Track record of growing enterprise accounts through expansion, upsell, or land-and-expand motions.
• Familiarity with sales qualification frameworks such as MEDDPICC or Command of the Message.

Benefits and work setup

• Fully remote position.
• Competitive compensation and equity package.