Senior Tech Program Manager, AWS Worldwide Public Sector Engineering (WWPSE)

What if your job was to prove that an AI-powered idea actually works - in weeks, not years - for the organisations that serve millions of people every day? We're looking for a Technical Program Manager who thrives at the intersection of generative AI, agentic systems, and real-world public sector challenges across Australia and New Zealand. You'll own the delivery of rapid engineering prototypes - most leveraging AI capabilities - that de-risk major technology investments for government agencies, healthcare systems, research institutions, and critical infrastructure providers. This is a hands-on delivery role, not a coordination one. You will work side by side with software engineers and solutions architects to scope, plan, build, and ship AI-driven solutions that directly influence multi-million-dollar customer decisions. If you enjoy moving fast, applying generative AI and machine learning to real problems, making architecture and trade-off decisions alongside engineers, and seeing your work in production within weeks - not months - keep reading. Key job responsibilities Engagement Ownership - Own delivery of 2–4 concurrent engagements from qualification through build to customer handoff - Translate business problems into prototyping charters with defined outcomes, timelines, and exit criteria • Make architecture and design trade-offs alongside engineers - own the technical outcome, not just the schedule - Lead sprint planning, backlog prioritization, and execution across short build cycles Pipeline & Qualification - Partner with sales and solutions architects to qualify opportunities against impact and feasibility - Lead Working Backwards workshops to define scope and success metrics Reuse, Scale & Handover - Architect for reuse across customers, verticals, and geographies; plan handover with transfer artefacts and code drops - Collaborate globally (NAMER, UKGI) to share patterns and adapt solutions across regions Regulated Environments - Navigate data sovereignty, health privacy, and government security requirements; clear compliance blockers for co-builds involving customer data Stakeholder Navigation & Impact - Primary interface between customer, account team, and engineering - aligning sales priorities with technical feasibility - Connect prototype outcomes to investment decisions; surface reusable patterns for service teams Technical Depth - Stay current on AWS AI/ML (Bedrock, SageMaker, agentic frameworks), serverless, and app modernization - Evaluate emerging GenAI, edge AI, and AI-assisted development patterns for public sector applicability A day in the life - You ship working software - not slide decks. Engagements end with a prototype answering real customer questions. - Variety and pace - AI health assistants one month, legacy modernization the next, in weeks-long cycles. - Technical ownership - design trade-offs alongside engineers; you own the outcome. - Direct impact - prototypes inform multi-million-dollar decisions for organizations serving millions. - Small team, outsized reach - high-autonomy work visible to senior leadership. - Build once, amplify many - solutions reused across countries and showcased at AWS events. - Global team - collaborating across time zones to share patterns and raise the bar. About the team A field-deployed AWS engineering team accelerating public sector outcomes through prototyping - with AI at the core. We build working systems that de-risk transformation programs and unlock cloud adoption for government organizations across Australia and New Zealand. Work spans agentic AI, application modernization, edge AI, and AI-assisted development. Small teams on 1-6 week cycles demand sharp scoping and tight engineering-sales-SA collaboration. Solutions built to transfer, not maintain - co-built with customers, architected for reuse, handover designed from day one. Aligned to health, transport, education, defence, and research, you build domain expertise across diverse technical problems.

Basic qualifications: - 5+ years of technical product or program management experience - 7+ years of working directly with engineering teams experience - 3+ years of software development experience - 5+ years of technical program management working directly with software engineering teams experience - Experience managing programs across cross functional teams, building processes and coordinating release schedules - Experience with AI/ML technologies