Lead Business Value Delivery Architect/Solution Architect - US

Sapiens•,

40d•Remote

About The Position

This role bridges the gap between presales and delivery, maintaining engagement across both functions. It spans Property & Casualty (P&C), Life, and potentially Reinsurance, with a specific emphasis on non-functional and operational requirements that are often under-invested in within the industry. The ideal candidate is deeply knowledgeable about insurance product suites and platform roadmaps, capable of conversing effectively with both senior management (e.g., Head of Claims) and technical teams (e.g., engineers), and is driven to ensure clients and internal teams remain committed to the agreed-upon outcomes.

Requirements

Track record designing or leading solution design in complex, enterprise insurance implementations, ideally spanning presales and delivery.
Ability to speak credibly to both a head of claims and an engineer, across P&C, Life, and Reinsurance.
Strong understanding of non-functional and operational requirements: performance, scale, availability, security, integration, operability, not only functional design.
Demonstrated ability to hold the professional and outcome vector, keeping internal teams and clients aligned to agreed business outcomes.
Experience with, or strong aptitude for, legacy to SaaS or core platform migration work.
Comfortable operating in a function that is still being built; process and tooling will be defined in parallel with the first deals.
Proficient in leveraging AI-driven tools and platforms to design, optimize, and scale enterprise solution architectures.

Nice To Haves

Ideally have hands-on experience with cloud-native platforms.
Proven track record working at Born-in-the-Cloud (BIC) companies, bringing modern SaaS delivery practices to a global enterprise environment.

Responsibilities

Ensure every signed program has a documented, client-agreed business outcome baseline, a joint definition of done, and go-live success criteria.
Surface and design non-functional and operational requirements upfront, preventing their discovery during the build phase.
Resolve platform gaps deliberately through core platform commitment or extension layer build, rather than allowing them to emerge during delivery.
Ensure delivery builds to the handed-over design with minimal rework due to scope or requirements ambiguity.
Contribute to measurable improvements in the SA group's processes, tools, and outputs to shorten implementation times.
Engage during the sales cycle to build product and industry context on the opportunity.
Frame solutions around client business outcomes, mapping client objectives to platform capabilities.
Establish a business outcome baseline with the client, defining measurable post-go-live capabilities.
Own the definition of done, jointly agreed with the client.
Explicitly cover non-functional and operational requirements (performance, scale, availability, security, integration, operability, support).
Feed into the implementation plan, defining the correct order of implementation and dependencies.
Own the resolution of platform gaps with Product and R&D, securing core platform commitments or designing extension layers.
Act as a deeper layer of expertise behind presales and industry experts.
Support bids with clearly stated assumptions.
Harden the solution against platform capabilities post-signing, steering towards standard configuration.
Hand over a clear, documented solution design to the delivery team and safeguard its integrity.
Hold internal teams and clients accountable to agreed business outcomes and their achievement.
Stay engaged through quarterly business reviews to identify outcome or value drift.
Apply the definition of done, ensuring projects are complete when clients can realize agreed-upon value.
Own migration outcomes through the analyse, dispose, bridge, and migrate framework.
Define migration value and KPIs with each client.
Serve as the first internal customer for AI in delivery, owning tools and usage standards.
Set precedence for conflicting inputs (signed document over email, etc.).
Define human verification requirements for AI-drafted work.
Identify what inputs do not state (tacit process, disagreements, edge cases).
Collaborate with the SA group to improve processes, outputs, and tools for faster, better implementations, including feedback loops.