Value Engineer

TL;DR

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. 

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.

• German-speaking

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

Why deepset

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.

Nice to have

• Demonstrates strong systems thinking paired with tactical execution, with sound judgment to choose the right approach at the right time.

What you will do1. : 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.

2. 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.
  
  

3. 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.
  
  

4. 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.
  
  

5. 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.
  
  

6. Represent the Customer Internally

• Bring structured feedback to Product and Engineering to support roadmap efforts in a way that balances signal and noise

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