Sales Engineering Expert - Evaluator

Mercor; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Mercor is partnering with a leading AI research organization to engage experienced sales engineers for a project focused on evaluating how well AI systems perform real-world technical sales work. You will define what excellent work looks like: designing task-specific grading criteria and scoring completed work samples with rigorous, well-reasoned written justifications.

Key responsibilities include designing precise grading criteria for pre-sales deliverables and scoring samples with detailed

Qualifications

• 4+ years of relevant experience as a Sales Engineer or related role.
• Deep fluency in the pre-sales craft: leading technical discovery, translating customer requirements into product solutions, delivering tailored demos, handling technical objections, supporting proofs of concept, and evaluating product fit and technical risk.
• Hands-on experience with technically complex B2B software — SaaS, cloud infrastructure, cybersecurity, data platforms, developer tools, or enterprise applications.
• Exceptionally strong written communication, with the ability to explain exactly why a piece of technical work would or would not land with both technical and business stakeholders.
• Detail-oriented, consistent, and comfortable having your judgment reviewed and calibrated against peers.
• Prior experience with AI training, evaluation, or human-data projects is a strong plus

Responsibilities

• Design precise, task-specific grading criteria for real-world pre-sales and solutions-engineering deliverables (technical discovery plans, tailored product demonstrations, proof-of-concept and technical evaluation plans, security questionnaires and RFP responses, integration/API/architecture explanations, and product-fit and technical-risk assessments)
• Score AI-generated and human work samples against those criteria, with detailed written justifications for every score
• Apply consistent, evidence-based judgment so scores are reproducible and defensible
• Incorporate structured feedback from senior reviewers and iterate quickly on your work

Skills

Sales engineering

Pre-sales

Technical communication

B2B software experience

Written communication

Job description

1. Role Overview

Mercor is partnering with a leading AI research organization to engage experienced sales engineers for a project focused on evaluating how well AI systems perform real-world technical sales work. Rather than producing deliverables yourself, you will define what excellent work looks like: designing task-specific grading criteria and scoring completed work samples with rigorous, well-reasoned written justifications.

2. Key Responsibilities

• Design precise, task‑specific grading criteria for real‑world pre‑sales and solutions‑engineering deliverables (technical discovery plans, tailored product demonstrations, proof‑of‑concept and technical evaluation plans, security questionnaires and RFP responses, integration/API/architecture explanations, and product‑fit and technical‑risk assessments)


• Score AI‑generated and human work samples against those criteria, with detailed written justifications for every score


• Apply consistent, evidence‑based judgment so scores are reproducible and defensible


• Incorporate structured feedback from senior reviewers and iterate quickly on your work

3. Ideal Qualifications

• 4+ years of relevant experience as a Sales Engineer, Solutions Engineer, Solutions Consultant, Pre‑Sales Consultant, or Technical Sales Consultant


• Deep fluency in the pre‑sales craft: leading technical discovery, translating customer requirements into product solutions, delivering tailored demos, handling technical objections, supporting proofs of concept, and evaluating product fit and technical risk


• Hands‑on experience with technically complex B2B software — SaaS, cloud infrastructure, cybersecurity, data platforms, developer tools, or enterprise applications


• Exceptionally strong written communication, with the ability to explain exactly why a piece of technical work would or would not land with both technical and business stakeholders


• Detail‑oriented, consistent, and comfortable having your judgment reviewed and calibrated against peers


• Prior experience with AI training, evaluation, or human‑data projects is a strong plus