At a Glance
- Tasks: Guide enterprise customers to success with AI solutions and drive value delivery.
- Company: Join deepset, a leader in applied AI with a focus on real-world impact.
- Benefits: Enjoy remote work, flexible hours, 30 days vacation, and competitive salary with stock options.
- Why this job: Shape the future of AI while working with cutting-edge technology and a passionate team.
- Qualifications: Experience in Sales Engineering or Customer Success, plus practical Python skills.
- Other info: Be part of a values-led organisation that prioritises craft, ownership, and collaboration.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We’re hiring a Value Engineer to guide enterprise customers from first conversation to long-term success. You’ll help Sales win the right deals, design solutions that work in the real world, ensure customers reach value quickly, and spot opportunities to grow the relationship. This role is a prescriptive, opinionated authority on which AI use cases make both business & technical sense by developing an account thesis and tying back to outcomes.
At deepset, you’ll work on AI that actually runs in production, powering real systems used by enterprises, governments, and highly regulated organisations. We operate at the sharp end of applied AI, solving hard problems around retrieval-augmented generation, performance, security, privacy, and on-premise and sovereign deployments, where reliability and trust truly matter. Open source is at our core as the team behind Haystack, while we also build enterprise-grade products for some of the most demanding customers in the world. We value craft, ownership, and outcomes over hype: small, highly-competent teams with real autonomy, direct access to decision-makers, and the opportunity to shape both product direction and how we work. We’re a values-led, human organisation that believes in challenge and care in equal measure, and we support flexible, remote-friendly ways of working with a globally minded team that comes together regularly to build, learn, and move fast, together.
What you will do:
- Value Discovery: Understand the Customer’s Needs
Lead early discovery to uncover goals, challenges, KPIs, and key stakeholders. Sparring partner with Enterprise Sales on overall deal quality and expansion opportunity, focused on winning as a team. - Solution Design: Creating the Right Solution
Translate customer needs into clear technical and business solutions. Build demos/POCs that prove value. Ownership of AI risk management across data readiness, feasibility, evaluation rigor, adoption and value realisation. Outline a plan that sets the customer up to win. - Value Delivery: Help guide to delivery team to customer value creation
Drive the plan to “first value.” Identify and execute on iterations without losing sight of key value metrics. Coordinate customer and internal teams so projects stay on track. Document architectures, runbooks, and train users so they can be self-sufficient. - Value Realisation: Measure Impact & Ensure Success
Track usage, performance, and business outcomes. Run check-ins/QBRs and help customers adopt the solution fully. Resolve escalations and ensure issues don’t repeat. - Value Expansion: Grow the Account
Spot expansion opportunities based on usage, pain points, and roadmap fit. Partner with Sales to build value cases and support forecasting. - Represent the Customer Internally: Bring structured feedback to Product and Engineering to support roadmap efforts in a way that balances signal and noise.
Requirements:
- Significant experience in Sales Engineering, Consulting/Implementation, or Customer Success for enterprise software.
- Practical Python skills for scripting and troubleshooting.
- Experience with AI/ML workflows (fine-tuning, data prep, model evaluation).
- Strong understanding of modern architectures (APIs, integrations, IAM/security; bonus for Kubernetes/Terraform/SSO/VPC).
- Ability to get hands-on with data, SQL, and light integrations.
- Strong project leadership and communication, including executive-level storytelling.
- Commercial awareness and a focus on measurable outcomes.
Nice to have:
- Demonstrates strong systems thinking paired with tactical execution, with sound judgment to choose the right approach at the right time.
Benefits:
- Remote-first setup with flexible hours & tech of your choice.
- 30 days vacation + extra days for family sick leave.
- Competitive salary & stock options for every team member.
- Monthly sports & mental health support allowance with Oliva.
- Annual learning & development budget.
- Monthly team socials & in-person meetups.
Founded in 2018, deepset builds open and enterprise-grade tools that help teams build AI with purpose. From Haystack, our open-source framework, to the deepset AI Platform, we give developers and organizations the building blocks to solve complex, high impact challenges with AI – with full control, transparency, and sovereignty. Backed by GV and Balderton, we’re growing the world’s production AI community and customer base solving challenges too critical to get wrong.
Value Engineer - UK in London employer: deepset GmbH
Contact Detail:
deepset GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Value Engineer - UK in London
✨Tip Number 1
Get to know the company inside out! Research deepset's products, values, and recent projects. This will help you tailor your conversations and show that you're genuinely interested in what they do.
✨Tip Number 2
Practice your storytelling skills. When discussing your experience, frame it in a way that highlights how you've helped customers achieve success. Use specific examples that relate to the role of a Value Engineer.
✨Tip Number 3
Network like a pro! Connect with current employees on LinkedIn or attend industry events. Building relationships can give you insider info and might even lead to a referral, which is always a bonus.
✨Tip Number 4
Don’t forget to follow up after interviews! A quick thank-you email reiterating your enthusiasm for the role can leave a lasting impression. Plus, it shows you’re proactive and keen to join the team.
We think you need these skills to ace Value Engineer - UK in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Value Engineer role. Highlight your experience in Sales Engineering or Customer Success, and don’t forget to mention any practical Python skills you have. We want to see how your background aligns with our needs!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We love candidates who can demonstrate their ability to design solutions that work in the real world, so share those success stories with us!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We appreciate a well-structured application that gets straight to the point, showing us why you're the right fit for the team.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at deepset!
How to prepare for a job interview at deepset GmbH
✨Know Your Customer's Needs
Before the interview, research common challenges and goals that enterprise customers face in the AI space. Be prepared to discuss how you would lead value discovery sessions to uncover these needs and how your experience aligns with helping customers achieve their KPIs.
✨Showcase Your Solution Design Skills
Prepare examples of how you've translated customer needs into effective technical and business solutions in the past. Think about specific demos or proofs of concept you've built that demonstrate value, and be ready to explain your thought process behind them.
✨Highlight Your Project Leadership Experience
Be ready to talk about your project management skills, especially in guiding teams towards delivering customer value. Share stories where you coordinated internal and external teams to keep projects on track and how you documented processes to ensure self-sufficiency for users.
✨Demonstrate Your Technical Know-How
Brush up on your practical Python skills and understanding of AI/ML workflows. Be prepared to discuss modern architectures and any hands-on experience you have with data, SQL, or integrations. This will show that you can get into the nitty-gritty when needed.