Senior Pre Sales Engineer, Monte Carlo

• Hands-on experience with enterprise AI and agent deployments. You’ve deployed agents in enterprise organisations — or worked closely enough with teams that do to understand the architecture, the failure modes, and the operational reality. You know what it takes to get an agent from demo to production
• Fluency in AI observability concepts. Traces, spans, evaluations, instrumentation — these are working vocabulary, not buzzwords. Experience with OpenTelemetry is highly prized, as is exposure to Databricks Genie, Snowflake Cortex, or similar enterprise AI platforms
• 5+ years in pre-sales, solutions engineering, or strategic technical account management within B2B AI-first companies and SaaS organisations — with meaningful experience in enterprise accounts. You’ve navigated procurement, infosec reviews, and multi-stakeholder buying committees
• Equal parts technical and business focused. You can whiteboard an agent architecture and hold a conversation with a VP of Data & AI about ROI and competitive positioning. Credible with engineers, effective with executives
• Self-directed and accountable. A lean US team with high-value accounts. You prioritise your own time, know when to escalate, and know when to push back
• Strong communicator across seniority levels. Equally comfortable in a technical deep-dive with a platform engineer and presenting a business case to a C-minus-1

Desirable

• The largest enterprises in the US are deploying agents into production right now — and discovering that trust, reliability, and observability are the difference between a pilot and a platform. We’re looking for a sales engineer who has lived that reality and can help our strategic customers navigate it
• Run technical sales cycles end to end. Own discovery, solution design, demos, POV execution, and technical close for opportunities within strategic US enterprises. Partner with Account Executives on commercial strategy; drive the technical win independently
• Sell into the agentic stack. Our customers are deploying agents on Databricks, Snowflake, and their own platforms. You’ll help them understand how to observe, trust, and improve those systems — from the data pipelines feeding agents, to the context they retrieve, the decisions they make, and the outputs they produce
• Drive POVs that convert. Design proofs of value with agreed success criteria, manage the evaluation, and deliver results that remove technical objections and accelerate the commercial close
• Build technical champions. Identify and develop the advocates inside each account who will carry Monte Carlo into the next budget cycle, platform decision, or executive review. Run briefings, workshops, and architecture reviews that position our platform as infrastructure
• Bring a technical point of view. Understand each customer’s data and AI architecture deeply — where agents run, how they’re instrumented, and where reliability breaks down. Bring that perspective to every account plan and QBR
• How we’ll measure success
• Technical win rate on POVs. POVs you run should convert. You set agreed success criteria upfront and deliver against them
• Technical execution against pipeline. Every opportunity properly scoped, proven, and technically closed
• Revenue growth. Still important — closed commitments should translate into growing consumption over time, and your technical work sets that trajectory