Senior Tech Program Manager, AWS Worldwide Public Sector Engineering (WWPSE)
Amazon · Sydney, New South Wales, AUS ·
- Seniority
- Senior
- Category
- Project management
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.
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.