At a Glance
- Tasks: Design and implement no-code AI workflows for enterprise clients in finance and legal sectors.
- Company: Join V7, a fast-growing AI platform backed by industry pioneers.
- Benefits: Competitive salary, commission structure, equity, and the chance to shape AI solutions.
- Other info: Be part of a dynamic team with opportunities for career advancement.
- Why this job: Make a huge impact in a high-growth startup with revolutionary AI technology.
- Qualifications: Experience in LLM projects, Python proficiency, and strong communication skills.
The predicted salary is between 160000 - 200000 £ per year.
Join V7 as the second Solutions Engineer in NYC to accelerate the growth of V7 Go, a no-code AI agent toolkit. You will bridge sales and product, designing sophisticated LLM workflows for enterprise clients in finance and legal sectors. This role is pivotal in scaling a product that 4x‑ed revenue last year.
Why this role is remarkable:
- Work with a high-growth startup backed by AI pioneers, including the minds behind Transformers and Gemini, at a company where revenue recently quadrupled.
- Huge technical impact as the second SE in New York, directly shaping how global enterprises deploy agentic AI for complex, multi-modal data processing.
- Total compensation includes a competitive base, a $30k commission structure, and equity in a fast-scaling platform processing tens of millions of documents.
Responsibilities:
- Lead technical discovery and POCs alongside Account Executives to design and implement custom no-code AI agent workflows for enterprise customers.
- Build robust Python-based data pipelines and prompt engineering solutions that integrate various LLMs like GPT, Claude, and Gemini into client environments.
- Serve as the primary technical point of contact for up to 10 concurrent projects, translating customer feedback into product requirements for the engineering team.
Qualifications:
- Experienced in delivering LLM-based projects, including API integration, prompt engineering, and measuring AI accuracy for enterprise-grade solutions.
- Strong technical background with Python proficiency and the ability to design complex cloud architectures and data pipelines for diverse stakeholders.
- Excellent communicator who can articulate a vision for AI solutions to both technical leads and business executives while managing multiple high-stakes accounts.
Required Skills:
- Python
- Cloud architectures
- Data pipelines
Required Languages:
- English
AI Solutions Engineer: LLM Pipelines & No-Code AI employer: Jack & Jill
V7 is an exceptional employer, offering a dynamic work environment in the heart of New York City where innovation thrives. As a pivotal member of a high-growth startup backed by AI pioneers, you will have unparalleled opportunities for professional development and technical impact, all while enjoying competitive compensation and equity in a rapidly scaling platform. Join us to be at the forefront of transforming human knowledge into trustworthy AI solutions, with a culture that values collaboration and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land AI Solutions Engineer: LLM Pipelines & No-Code AI
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech space, especially those who work at V7 or similar companies. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your LLM projects and Python pipelines. When you get the chance, share this during interviews to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of cloud architectures and data pipelines. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the V7 team.
We think you need these skills to ace AI Solutions Engineer: LLM Pipelines & No-Code AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Solutions Engineer role. Highlight your experience with LLMs, Python, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're excited about joining V7 and how you can contribute to our mission. Be sure to mention your experience in no-code AI and how it relates to the role.
Showcase Your Technical Skills:In your application, don't shy away from showcasing your technical skills. Mention specific projects where you've built data pipelines or integrated APIs. We love seeing concrete examples of your work!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Jack & Jill
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models like GPT, Claude, and Gemini. Be ready to discuss how you've integrated these into projects before, as well as any challenges you faced and how you overcame them.
✨Showcase Your Python Skills
Since Python proficiency is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your approach to building data pipelines, so have some examples ready.
✨Communicate Clearly
As an AI Solutions Engineer, you'll need to bridge the gap between technical and non-technical stakeholders. Practice explaining complex concepts in simple terms, and think of examples where you've successfully communicated with both tech leads and business executives.
✨Prepare for Technical Discovery Scenarios
Expect to engage in discussions about technical discovery and proof of concepts (POCs). Prepare to outline how you would approach designing no-code AI workflows for enterprise clients, and think about how you would gather and translate customer feedback into actionable product requirements.
