Sr. Sales Engineer (Forward Deployed Engineer - Pre Sales)
J
JobgetherAI observability
Based in United StatesFull-TimeSenior
SalaryBase salary range of $240,000–$270,000 annually, plus eligibility for commission.
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Job Details
- Experience
- 3+ years of experience in pre-sales, solutions engineering, or strategic technical account management within B2B AI-focused or SaaS organizations, with meaningful enterprise experience.
- Required Skills
- SnowflakeDatabricks
Requirements
- Have hands-on experience deploying enterprise AI or agent-based systems, or working closely with teams taking agents from experimentation into production.
- Bring 3+ years of experience in pre-sales, solutions engineering, or strategic technical account management within B2B AI-focused or SaaS organizations, including meaningful enterprise experience.
- Understand AI observability concepts, including traces, spans, evaluations, and instrumentation.
- Navigate enterprise procurement processes, information security reviews, and complex multi-stakeholder buying committees.
- Have a professional background in data, observability, agent trust, or agent-focused products, with direct experience in one or more of these domains.
- Be able to whiteboard AI or agent architectures and communicate ROI and competitive positioning to senior executives.
- Communicate technical information to audiences ranging from platform engineers to senior data and AI leaders.
- Prioritize and manage high-value accounts independently, recognize when to escalate, and challenge assumptions when necessary.
- Experience with OpenTelemetry is highly valued.
- Experience with Snowflake, Databricks, dbt, Airflow, BigQuery, or similar modern data technologies is preferred.
- Experience with data observability or data quality, enterprise account expansion, MEDDPICC or similar sales frameworks, multi-country enterprise sales, or hands-on prototyping during sales cycles is a plus.
Responsibilities
- Own technical sales cycles from discovery and solution design through demonstrations, proofs of value, and technical close within strategic enterprise accounts.
- Partner with Account Executives on commercial strategy while driving the technical win and resolving technical objections.
- Help customers understand how to observe, trust, and improve AI and agent-based systems across data pipelines, retrieved context, agent decisions, and outputs.
- Design and manage proofs of value with defined success criteria, oversee evaluations, and deliver measurable results.
- Develop technical champions through workshops, briefings, architecture reviews, and executive engagements.
- Assess customer data and AI architectures, including agent environments, instrumentation, and reliability challenges.
- Contribute technical insight to account plans and business reviews and support technical execution across the sales pipeline.
- Help scope, validate, and position technical opportunities for customer adoption and expansion.
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