Value Engineer - Applied AI

SAPIENS•Remote, OR

12d•Remote

About The Position

The Value Engineer – Applied AI sits at the intersection of sales, product, customer success, and enterprise AI deployment. This is a hybrid role that blends traditional value engineering with the hands-on, embedded delivery model of a forward deployed AI engineer. You will help customers understand, quantify, and realize the measurable business value of Sapiens' AI-powered solutions — and then roll up your sleeves to help them actually get there. You will partner with account teams and executive stakeholders to build compelling value cases, accelerate deal cycles, and go deeper with customers to prototype, deploy, and iterate on AI-driven workflows that deliver real outcomes.

Requirements

7+ years in value engineering, management consulting, financial analysis, solution consulting, or a related strategic role.
Demonstrated experience deploying or implementing AI/ML solutions in enterprise environments — not just advising on them.
Strong analytical and financial modeling skills (ROI, TCO, KPI modeling).
Exceptional communication skills, including executive-level storytelling, live demos, and technical presentation.
Ability to translate complex AI and technical capabilities into concrete business outcomes.
Experience engaging with C-suite stakeholders in enterprise environments.
Hands-on fluency with LLMs, prompt engineering, and AI product development — comfort building as well as advising.
Comfort working cross-functionally in a fast-paced SaaS or technology environment.

Nice To Haves

Experience in insurance, financial services, or another regulated enterprise vertical is a strong plus.

Responsibilities

Partner with sales teams to uncover customer pain points, strategic initiatives, and AI readiness.
Lead discovery sessions with customer executives to map business processes, KPI gaps, financial drivers, and high-value AI use cases.
Build tailored business cases, including ROI models, TCO analysis, and AI impact scenarios that quantify the value of intelligent automation and decision support.
Present value insights and AI deployment strategies to senior stakeholders in a compelling and consultative way.
Embed with customers during the sales cycle to prototype AI-powered workflows and demonstrate value before the ink dries.
Align Sapiens' AI capabilities to measurable business outcomes tied to customer priorities.
Collaborate with product experts, solution consultants, and engineering teams to map AI value drivers to platform features and deployment patterns.
Support competitive positioning by quantifying AI differentiators and the financial benefits of an AI-native delivery model.
Provide thought leadership during key engagements, executive briefings, and AI value workshops.
Build working proofs-of-concept and demonstration environments using Sapiens' AI tools to make the value tangible, not theoretical.
Embed directly with strategic customers post-sale to accelerate AI adoption and time-to-value.
Work inside customer environments to build, iterate, and ship production-ready AI applications on the Sapiens platform.
Identify repeatable AI deployment patterns across customer engagements and codify them into reusable playbooks for the broader team.
Act as the connective tissue between the customer's operational teams and Sapiens' product and engineering organizations — translating field insights into product direction.
Operate with autonomy and thrive under ambiguity; this role requires someone who can define what good looks like, not just follow a playbook.
Partner with Customer Success to track actual AI-driven outcomes against proposed value models.
Build value realization reports for QBRs, renewals, and expansion opportunities — grounded in real deployment data, not projections.
Identify patterns across accounts to refine value frameworks and contribute field-level insights to the product roadmap.
Maintain and evolve ROI calculators, AI impact benchmarks, and value frameworks specific to the insurance industry.
Train sales and customer-facing teams on value-selling methodologies and AI deployment best practices.
Conduct market and industry research to inform benchmarking and persona-specific AI value narratives.
Stay current on the latest LLM capabilities, agentic AI frameworks, and enterprise deployment patterns — and bring that knowledge into every customer engagement.