CS Engineering Lead
Team8
Description
Insait builds AI agent products for financial services — banks, insurers, and lenders.
Deployments are deeply integrated, highly customized, and often on-prem or hybrid.
We deliver results, not demos.
About the team
Financial services is one of the hardest environments to deploy AI in. Regulated, complex, and deeply integrated — banks, insurers, and lenders don’t buy software, they buy outcomes. Getting an AI agent to perform reliably in that context isn’t a configuration exercise. It takes technical depth, close iteration with the client, and the discipline to keep pushing until it works in production.
That’s why we’re building a dedicated Customer Engineering team. These aren’t generalist implementers — they’re specialists who own the full arc of an agent deployment: configuring the core components, integrating with client systems, stress-testing behaviour, and making sure the agent holds up when real customers are on the other end. They work directly with the client’s technical teams, know Insait’s platform inside out, and don’t hand off accountability until the job is genuinely done.
About the role
In this role, you take full ownership of how Insait delivers — across every client, every deployment, every market we operate in. You’ll sit at the intersection of technical depth and executive relationship, translating what banks and lenders actually need into working AI agents that perform in production. The job is to make complex things land: on time, at quality, with clients who feel it.
You’ll be deeply embedded across the business — working with Sales on scoping, Engineering on product gaps, and CS on what happens after go-live. What you learn in the field shapes what we build next. We’re looking for someone who can run at pace, hold a high bar, and build the kind of delivery muscle that compounds as we grow.
What you’ll own
- End-to-end delivery: scoping, onboarding, integration, and go-live across all clients
- Time-to-value — the #1 KPI. Drive it down continuously through better methodology, tooling, and team execution
- Team leadership: hire, coach, and set a high bar for Customer Engineers; build capacity as we scale
- Delivery methodology: project frameworks, QA standards, launch readiness checklists, and escalation paths
- Commercial model: scoping, effort estimation, SOWs, and delivery margins
- Executive-level client engagement: define success criteria, align on security/compliance constraints, drive delivery against timelines
- Cross-functional handoffs with Sales (scoping), Customer Success (post-go-live), and Engineering (product gaps)
- Platform influence: identify recurring gaps from deployments and drive prioritization with Product and Engineering
- IS/SI partner program — certifying and enabling external partners to extend delivery capacity globally
Requirements:
- 8+ years in Professional Services, field engineering, or technical delivery — with 3–5+ years of managerial experience.
- Hands-on background: you’ve done complex implementations yourself, not just managed people who did
- Strong technical foundation — comfortable with APIs, integrations, and complex system architecture
- Startup experience at a company that scaled — you know how to build process without bureaucracy
- Commercial instincts: scoping, pricing, and owning delivery margin
- Enterprise client management in regulated or complex industries
Big advantage
- Background in AI agents, LLM-based products, or conversational AI
- Delivered to financial services clients — banks, insurers, lenders
- Experience with enterprise SaaS integrations and security/compliance considerations
- Experience scaling a delivery function from high-touch execution to repeatable playbooks
- Experience building or enabling an IS/SI partner delivery program
- Hebrew — not required but a real plus