Description Encore AI builds conversational AI agent platforms for banks, insurers, lenders, and investment houses across Israel, Australia, and the US. We're looking for our first Deployment Strategist in ANZ , to own the bridge between what our AI agents can do and what our clients actually need in production. This is not a classic onboarding or support role. You'll sit at the intersection of client strategy, prompt/flow engineering, and delivery ownership — translating a bank's or insurer's operational reality into a working, production-grade AI agent, and translating field learnings back into product and platform improvements. You'll work across our client base in Australia. What You'll Own Deployment ownership end-to-end. Take a client engagement from kickoff through go-live and into steady-state, owning the outcome — not just the handoff. Solution design with clients. Run discovery and design workshops with client stakeholders (product owners, compliance, ops leads) to translate business requirements into agent flows, node logic, and conversation design. Hands-on configuration. Work directly in the Encore AI platform — flow JSON, conversation/collect/end nodes, prompt engineering — to build and refine agents, rather than only spec'ing requirements for someone else to build. Executive-level communication. Present progress, risk, and roadmap to client stakeholders ranging from project leads to C-suite, across our Israeli, Australian, and US accounts. Organizational readiness. Help clients (often regulated financial institutions) navigate the process and change-management side of adopting an AI agent — not just the technical rollout. Field-to-product feedback loop. Be the connective tissue between what clients need and what Encore AI builds — surfacing patterns across accounts to Product and Engineering. Risk and escalation management. Identify delivery risk early (timeline, scope, technical blockers) and manage it proactively with both client and internal stakeholders. Reusable playbooks. Build documentation, QA frameworks, and implementation patterns that make the next deployment faster than the last. Requirements 3–6 years in a client-facing, technical delivery role — implementation, deployment, solutions engineering, or technical customer success — ideally at an AI/LLM, SaaS, or enterprise software company. Experience that maps to one of these profiles: Delivery/deployment lead at a company shipping AI or data products into production for enterprise clients. Solutions engineer or technical PM who moved toward the client and business side. Strategy or process consultant who wants to own outcomes rather than hand off recommendations. Comfort with ambiguity and technical depth. You don't need to write production code, but you should be comfortable getting into flow logic, JSON configs, and prompt structure yourself. Financial services familiarity is a strong plus — understanding of banking, insurance, or investment workflows, or regulatory/compliance context (KYC, SLAs, risk sign-off processes). English fluency required; You'll work across Israeli, Australian, and US accounts — most client-facing work happens in English. Executive presence — able to run a room with a client's VP or C-suite as comfortably as a technical working session. Bias toward ownership. Low ego, high follow-through; you take feedback directly and don't need things handed to you fully scoped. Nice to Have Prior experience with LLM prompt engineering or conversational AI design specifically (not just general software implementation). Experience working with regulated industries beyond finance (healthcare, insurance) where compliance and audit trails shape delivery.