Sales Engineer

InterSystems
Windsor
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Senior Machine Learning Engineer (Outfits)

Senior Machine Learning Engineer (MLOps)

Head of Machine Learning (Recommendations, AI Stylist & Search)

Lead Data Scientist

Data Scientist Intern (PhD level)

InterSystems Corporation, a leading provider of data solutions for industries with critical needs like healthcare, financial services and supply chain , is seeking candidates for its UK Sales Engineering Group. The role is client-facing, fast-paced, wide-ranging and challenging. It requires a mixture of application development and deployment skills, hands-on coding and problem-solving, presentation skills, sales awareness, and business acumen. Regional travel is extensive.

Responsibilities:

  • Coordinating with InterSystems' Account Representatives and all other departments to ensure a close, long-term relationship with our clients
  • Working closely with System Integrators and Project Managers, especially during the early stages of adoption and technically challenging projects, to ensure successful implementations
  • Recommending technical architectures, model design, development patterns, migration strategies, upgrade procedures, and operational best practices
  • Designing, building, and presenting Proofs of Concept (PoCs) to prospects and partners
  • Delivering standard and customized on-site training in a classroom environment
  • Supporting our clients during beta test programs or pre-launch activities
  • Supporting marketing activities at trade shows, conferences, seminars etc.
  • Keeping up-to-date with InterSystems products and contemporary IT industry developments (including competitive products) and undertaking any relevant self-development or training.
  • Creating prototypes and coordinating with product management to enhance product offerings based on client desires/needs
  • Writing competitive proposals, solution overviews, sales collateral, etc. to support pre-sale efforts

Qualifications/ Nice-to-Haves:

  • 4+ years of experience as a software developer or related role(s)
  • Personal presence to establish yourself as a trusted advisor to development and delivery managers and senior architects
  • Outstanding interpersonal, communication, and presentation skills
  • Strong technical and business writing skills
  • Proven business analysis and problem-solving skills
  • Demonstrated expertise in troubleshooting
  • Demonstrated experience with most/all of the following
    • Relational or non-relational databases using SQL or NoSQL
    • Data Engineering skills using Python
    • Modern Analytics architectures - Data Lakes /Data fabrics/Data mesh.
    • Machine Learning and Generative AI use cases
    • HTML, JavaScript, Angular
    • XML, XSLT, JSON, SOAP, REST
    • Cloud hardware services, containers, kubernetes, etc.
    • Windows, Unix/Linux, MAC OS X
    • API Management
  • Healthcare protocol experience (FHIR, HL7) a plus

Education:

  • BS in Computer Science or equivalent technical degree

 

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.