Senior Software Engineer (AI)

At Zuora, we help businesses grow smarter and adapt faster. Our platform powers modern business models — from subscriptions and usage-based pricing to AI-driven and outcome-based offerings — helping companies launch new products, automate complex billing, and unlock predictable, recurring revenue. We’ve led the Subscription Economy for more than a decade and are evolving by building the definitive platform for quote to cash, enabling companies to monetize their products and services with an adaptable, AI-ready foundation.

About the role

Zuora is seeking a Senior Software Engineer to architect and scale our Agentic Deal Desk product. In this high-impact individual contributor role, you will build resilient, high-throughput Java microservices alongside the underlying AI agent harness — the runtime scaffolding, execution loop, tool dispatch system, and state management engine that converts non-deterministic LLMs into reliable, enterprise-grade deal-desk agents.

Schedule

This role is based in our Foster City, CA office and follows a hybrid work model. Team members are expected to work onsite three days per week.

Responsibilities

• Agent Harness Engineering: Build and own the core agent harness layer, including the execution loop (ReAct/Plan-Act), state persistence, dynamic prompt assembly, output schema validation, and retry mechanisms.
• Tool Dispatch & Sandboxing: Design safe tool-execution runtimes and schema-validated function dispatchers that allow agents to execute complex deal operations, policy checks, and pricing adjustments securely.
• Context & Memory Management: Engineer context compaction, short-term session scratchpads, and long-term memory retrieval pipelines (RAG/vector search) to eliminate context degradation during multi-turn deal negotiations.
• Guardrails & Feedback Loops: Build computational and inferential feedback sensors (evaluators, deterministic policy linters, and verification checks) to enforce strict margin guardrails, discount limits, and compliance rules.
• Backend Architecture: Design low-latency, event-driven Core Java microservices to back the harness, driving state transitions, audit logs, and integration with Zuora Billing and CRM platforms.
• Technical Leadership: Set technical standards for agent harness design, drive evaluation/eval-driven development practices, and mentor senior engineers across squads.

Requirements

• Core Java Mastery: 8+ years of hands-on experience in modern Java (17+), JVM internals, concurrency models, Spring Boot, and cloud-native distributed architecture.
• Agent Harness & Runtime Systems: Deep experience building the infrastructure surrounding LLMs — agent loops, state-machine tracking, tool calling/dispatch systems, context window management, and structured output parsing.
• Agentic Frameworks & AI Tooling: Practical experience with LangGraph, CrewAI, AutoGen, LlamaIndex, or custom in-house agent orchestration runtimes and vector databases (e.g., Pgvector, Pinecone).
• Distributed Infrastructure: Heavy background in event-driven architecture (Kafka/RabbitMQ), high-performance caching (Redis), relational databases (PostgreSQL/MySQL), and REST/gRPC API design.
• Cloud & Runtime Security: Experience with AWS, Docker/container isolation, Kubernetes, and securing agent execution pathways against improper tool invocations or prompt injection.

Qualifications

• AWS Agentic Enablement: Production experience leveraging Amazon Bedrock Agents (Action Groups, Knowledge Bases, Multi-Agent Collaboration) and Guardrails for Amazon Bedrock to enforce policy boundaries and tool permissions.
• Serverless Agent Scaffolding: Experience utilizing AWS Lambda, Step Functions, DynamoDB, and ECS/Fargate for isolated tool-execution environments, persistent session state checkpointing, and agent workflow orchestration.
• AWS AI Observability & Evals: Familiarity with continuous agent monitoring, trace/span evaluation frameworks (e.g., Amazon Bedrock AgentCore Evaluations, CloudWatch), and LLM-as-a-judge pipelines for non-deterministic applications.
• Domain Expertise: Experience in Enterprise Deal Desk operations, revenue operations, quote-to-cash workflows, dynamic pricing engines, or high-volume SaaS approval chains.

Benefits

• Competitive compensation, variable bonus and performance-based reward opportunities, and retirement programs
• Medical insurance
• Generous, flexible time off, plus paid holidays, wellness days, and a company-wide year-end break
• Paid parental leave (including fully paid leave for eligible employees, subject to local policy)
• Learning & development stipend to support ongoing growth
• Opportunities to volunteer and give back, including charitable donation matching where available
• Mental wellbeing resources and support

Benefits may vary by location; details will be shared during the interview process.

Pay

The base pay for this position ranges from $164,800 to $226,600 USD annually. A candidate’s final base salary will be determined based on qualifications, job-related knowledge, prior experience, specific and unique skills, location, internal equity, and internal budget.