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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.
Job Responsibility:
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
Maintain accurate CRM and customer plans
Requirements:
8+ years 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
Demonstrates strong systems thinking paired with tactical execution, with sound judgment to choose the right approach at the right time