Staff AI Platform Engineer
Pushpay
Salary undisclosed
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Description
The Role in 60 Seconds
Most companies are still experimenting with AI wrappers in local environments. At Pushpay, we are building production-grade agentic systems that directly amplify how our entire engineering organization builds, ships, and operates software.
As a Staff AI Platform Engineer, you will operate with significant autonomy to architect, run, and scale our internal agentic platforms and developer tooling (like PR review agents, SDLC copilots, and context engines). You won't just build these systems—you will own their operational discipline, cost governance, evaluation suites, and reliability in production, acting as a force multiplier for every engineer across Pushpay.
Why This Role is Different
True Engineering Leverage: You aren't building internal gimmicks. You are designing systems that fundamentally transform our SDLC and reduce friction for every product team.
Production-Grade Non-Determinism: You treat agents as distributed, operational workloads—implementing token budgets, trace-level observability (OTEL, Langfuse), SLOs/SLIs, and eval-driven regression testing before code hits main.
Influence Without Dictatorship: You won't enforce top-down mandates. You will drive org-wide adoption of tools like Claude Code and custom MCP implementations through technical credibility, pairing with teams, and building platforms engineers want to use.
What You'll Do
Architect & Build Agentic Systems: Design internal supervisor loops, router patterns, and state machines using the Claude Agent SDK, AWS Bedrock, and frameworks like LangGraph.
Run Workloads at Scale: Establish SLOs for agent success rates, latency, and token efficiency. Take point on observability, prompt versioning, and incident response when agents misbehave or hallucinate.
Elevate Developer Experience: Identify SDLC bottlenecks, optimize build/CI performance, refine local dev setups (LocalStack, .NET Aspire), and tune AWS serverless architectures (Lambda cold-starts, SnapStart).
Set the Bar for AI Safety & Quality: Define reusable component models, context retrieval (RAG) architecture, and guardrails to ensure autonomous systems degrade safely.
What We Are Looking For
8+ Years in Software Engineering with significant time spent as a technical lead in Platform, Infrastructure, or DevEx.
Production Agentic Experience: You have actually operated non-deterministic LLM/agentic workloads in production—managing cost governance, tracing, and eval pipelines, not just building prototype wrapper apps.
Backend & Cloud Mastery: Deep proficiency in C# or Python paired with strong AWS cloud-native expertise (Lambda, API Gateway, Bedrock, IAM/KMS).
Developer Empathy & Leadership: A track record of driving tool adoption and technical standards across multiple teams through pairing, mentorship, and clear communication rather than authority.
Tech Stack You'll Touch
Claude Agent SDK • AWS Bedrock • LangGraph / LangChain • OTEL • Langfuse • New Relic • C# / .NET • Python • AWS Lambda • .NET Aspire • LocalStack
Ready to build the platform that powers the future of our engineering organization?
Apply now to join Pushpay's Enablement team as our Staff AI Platform Engineer!
You MUST be eligible to work in NZ to be considered for this role.
About this role
Pushpay is moving beyond AI experimentation into production-grade agentic systems that directly improve how their entire engineering organization builds and ships software. As Staff AI Platform Engineer, you'd architect and operate internal agent platforms—PR review systems, SDLC copilots, context engines—with full ownership of their reliability, cost, observability, and performance in production. This isn't a prototype role; you'd be designing systems that reduce friction across every product team and act as a force multiplier for hundreds of engineers.
The work spans architecture (Claude Agent SDK, LangGraph, AWS Bedrock), operational discipline (SLOs, token budgets, trace-level observability via OTEL and Langfuse), and developer experience optimization (CI performance, local dev tooling, serverless tuning). You'd also set safety and quality standards through RAG architecture, guardrails, and eval-driven testing. Success means driving adoption through technical credibility and pairing with teams rather than top-down mandates.
This role demands 8+ years in software engineering with substantial platform, infrastructure, or DevEx leadership experience, plus genuine production exposure to non-deterministic LLM workloads—managing costs, tracing, and evaluation pipelines, not just building wrappers. You'll need deep backend chops (C# or Python) and strong AWS cloud-native skills. The position is in-office in Auckland and requires NZ work eligibility.
How this employer is doing
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Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable Staff AI Platform Engineer postings in Auckland, and analyze any offer before you accept it.
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