Technical Sales Engineers / Solutions Engineers – AI & ML

Bristol
11 months ago
Applications closed

Related Jobs

View all jobs

Global Banking & Markets - Data Scientist / Machine Learning Scientist, Marquee Sales Strats - Associate

Senior Machine Learning Engineer (MLOps)

Senior Machine Learning Engineer (Outfits)

Senior Machine Learning Engineer

Data Scientist (Recommendation)

Senior Simulation Engineer (Data Science)

Technical Sales Engineers / Solutions Engineers – AI & Machine Learning

Location: Remote UK with UK travel

Are you passionate about AI, machine learning, and driving real business impact? Do you thrive at the intersection of technology and sales? If so, this is your opportunity to join an industry-leading company shaping the future of AI-powered solutions.

Why Join Us?

ARCA is partnering with a cutting-edge AI company at the forefront of artificial intelligence and computer vision. This is more than just a sales role - it’s a chance to work with revolutionary AI technology, engage with leading enterprises, and drive digital transformation in an ever-evolving industry.

Your Role

As a Technical Sales Engineers / Solutions Engineers, you will be a key player in our growth, helping businesses understand and unlock the power of AI. Your responsibilities will include:

Driving Sales & Engagement – Connect with potential clients through email, calls, and social media, introducing our AI-driven solutions and assessing their needs.
Technical Consultation – Collaborate with customers to define project scopes, solve technical challenges, and maximize the value of AI implementations.
Customer Enablement – Deliver engaging webinars, presentations, and training sessions tailored to diverse audiences.
Sales Strategy & Business Development – Identify and develop new business opportunities, generating high-quality, sales-approved leads.

Demos & Presentations – Lead impactful technical demos that showcase the capabilities of AI and machine learning in solving real-world problems.
Cross-Functional Collaboration – Work closely with R&D, Sales, and Account Executives to align solutions with market needs and customer demands.
Market Insights – Report on customer challenges, competitive trends, and new opportunities to drive strategic growth.

What We’re Looking For

We want a high-energy, target-driven sales professional who can bridge the gap between complex AI technology and business value. The ideal candidate will have:

✔ 4+ years of experience in technical sales
✔ A strong track record in B2B sales, with a results-oriented mindset and a passion for closing deals.
✔ Excellent communication skills, capable of simplifying complex AI concepts for non-technical stakeholders.
✔ Nice to have: A Bachelor's degree in a technical field or equivalent hands-on experience.
✔ Nice to have: Familiarity with AI, computer vision, and machine learning markets.

What’s in It for You?

Work with groundbreaking AI solutions at the forefront of innovation.
Join a global team making an impact across industries.
Be part of an exciting, fast-growing company where your contributions matter.

Apply Now!

If this sounds like the opportunity you’ve been looking for, we’d love to hear from you! Submit your application today and take the next step in your AI sales career

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.