Pre-Sales Engineer (for Weather-Dependent Energy Trading)

Posted 9 Days Ago
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Zürich
Senior level
Artificial Intelligence • Software
The Role
The Pre-Sales Engineer role at Jua involves demonstrating the AI-powered weather forecasting platform's impact on weather-dependent energy trading. Responsibilities include leading technical sales processes, developing customer-specific workflows, and serving as a key advisor during engagements. The role demands collaboration with sales and engineering teams, along with a customer-centric approach to convey complex technical concepts clearly to non-technical clients.
Summary Generated by Built In
Overview

Jua's mission is to create artificial general intelligence (AGI). Our product uses a foundational Earth systems model to predict atmospheric events. It’s more accurate, faster, and updates more frequently than current weather models, making it valuable for traders in weather-dependent power markets. These benefits are crucial during extreme weather events like hurricanes and cyclones. As we scale the model, more applications will become possible, including wildfire, flood, and vegetation prediction.
By joining our talented multidisciplinary team, you'll help shape our culture of ambition, transparent communication, and rapid iteration. We offer exciting challenges, creative freedom, fair pay, and generous stock options.

What we’re looking for

As a Pre-Sales Engineer, you will play a key role in demonstrating the impact of our AI-powered weather forecasting platform, helping customers see how Jua’s technology can revolutionize weather-dependent energy trading. You will bridge the gap between technical and non-technical stakeholders, showcasing the full potential of our technology to solve real-world challenges. This role is critical in guiding prospective clients from initial engagement to successful adoption, ensuring they receive exceptional support. 


Responsibilities and tasks

  • Lead and manage the technical aspects of the sales process, including conducting in-depth product demonstrations, webinars, trial implementations, and proof of concepts (PoCs), to showcase Jua’s capabilities and tailor solutions to client needs

  • Collaborate with the sales team to understand client needs and develop tailored solutions

  • Develop customer-specific workflows, integrating Jua’s platform into their operational processes

  • Serve as the key technical advisor during sales engagements, answering customer inquiries and providing technical insights

  • Gather customer feedback and share insights with product and engineering teams to drive continuous improvement

  • Stay up-to-date with the latest advancements in geospatial data, weather forecasting, and AI to effectively communicate product differentiators and market trends

  • Travel occasionally within Europe to engage with prospects and clients in person

Need-to-have

  • A highly technical individual with 5+ years of experience in pre-sales engineering, solutions engineering, or similar roles

  • Passionate about AI, machine learning, and data-heavy platforms, with hands-on experience in these areas

  • Customer-centric mindset with a deep curiosity for understanding challenges and the boldness to influence product roadmaps

  • Proven track record of collaborating with sales teams to close complex deals and ensure seamless technical integration

  • Strong communicator capable of translating complex technical concepts into clear business value for non-technical audiences

  • Experienced in managing Proof of Concept (POC) projects and working closely with customers on technical implementations

  • Ability to work cross-functionally with sales, product, and engineering teams to ensure a smooth customer experience

  • Solutions-driven, detail-oriented, and focused on customer satisfaction, with a proactive problem-solving attitude

  • Willingness to travel occasionally to support sales efforts and meet with clients

  • Experience in at least one of the following domains: AI, machine learning, energy, weather technology, or meteorology

  • Excellent verbal and written communication skills in English

  • Comfortable working in a fast-paced startup environment and adaptable to changing needs


Nice to have

  • Experience in collaborating with customers to develop tailored solutions, using Python to configure product features and demonstrate key functionalities

  • Ability to assist customers in writing and modifying basic Python scripts to effectively test and validate product use cases

  • Bachelor’s or Master’s degree in Geospatial Science, Meteorology, Data Science, Engineering, or a related field

At Jua, we foster a performance culture and value people who embody our beliefs of service and adventure. We prioritize agility, operating at the highest clock speed to adapt quickly to change. We innovate on behalf of our users and leverage data supremacy to maintain our competitive edge. Through clear communication and fact-based decision-making, we ensure alignment in our pursuit of excellence. With these principles, we aim to create a customer-focused, value-centric organization that sets new standards in the industry. We value the unique perspectives that each individual brings to the table and believe that embracing diverse backgrounds and experiences enriches our collective journey towards growth and success.

Top Skills

AI
Machine Learning
The Company
HQ: Schwyz
42 Employees
On-site Workplace
Year Founded: 2022

What We Do

Jua.ai - Accuracy beyond expectation. Use beyond belief. The world's first end to end deep learning model for weather forecasting, delivered on an intuitive platform for anyone to customise it. Startups, governments and large companies alike can now develop global, high frequency and high accuracy weather models within days.

Jua’s mission is focused on achieving artificial general intelligence (AGI) through a deep exploration of physics, the universe, and their interaction with the human civilisation. We are initially building the world's largest AI weather forecasting model so far and - to our knowledge - the first truly end to end one. This will help energy companies deal with weather volatility by way of significantly better and faster prediction as well as much more flexible extrapolation of insights.

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