Senior Staff Engineer Intuit Agent Ready Platform, PDX

Overview

ARP assesses if Intuit internal platforms are agentic-ready for end-to-end AI agent development. Its Eval engine normalizes top use cases, spawns agents in virtualized environments, executes plans, auto-files issue for friction (e.g., missing docs/APIs), and re-runs checks on CI/CD deploys to prevent regressions. This role belongs to the Core Platform Framework team, which builds the Eval platform and requires research-minded engineers focused on agent orchestration and LLM tooling, distinct from the Operations/Adoption team.

Responsibilities

The selected responsibilities for the Senior Staff Engineer role encompass leading and driving key architecture initiatives for the Eval platform:

• Core Platform Architecture: Owning and evolving the virtualization/harness layer, the agent plan-then-execute engine, and the friction detection and auto-ticketing pipeline.
• Model Orchestration & Cost Efficiency: Transitioning from single static models to dynamic, step-level orchestration that routes tasks to cost-effective models (including open-source options and Claude) while monitoring cost and performance per step.
• Telemetry & Auditability: Designing scalable logging, cost, and telemetry systems to ensure full auditability and cost accountability for agent runs.
• Use-Case Normalization: Setting technical standards to normalize agent-readable use cases across differently-documented capability platforms.
• Cross-Team & Strategic Collaboration: Partnering with capability, operations, and adjacent platform teams on friction reporting, PRD-to-action pipelines, RAG-backed architecture context, and OPA policy validation.
• Roadmap Leadership & Governance: Guiding the roadmap from foundational tooling (plugins, RBAC, alerting) to automation (auto-fix agents, continuous re-runs) and governance visibility.
• Mentorship & Technical Standards: Mentoring engineers and elevating engineering standards through design reviews, architecture documentation, and hands-on contributions.

Required:

• 12+ years of software engineering experience, focused on large-scale distributed systems or developer platforms.
• Hands-on experience building or operating LLM-agent systems (orchestration loops, tool use, plan-and-execute patterns).
• Strong systems programming background (Python, Java) with virtualization, sandboxing, or IaC experience.
• Proficiency in Python, Java, Spring Boot, GraphQL, and React.
• Applied AI and prompt design skills for reliable, cost-aware LLM behavior.
• Proven Staff+ capability setting cross-team technical direction.
• Comfort navigating ambiguity in a research-driven, next-gen engineering environment.

• Building or contributing to LLM or agent evaluation/benchmarking frameworks.
• Policy-as-code , RAG pipelines, or vector databases for enterprise agent grounding.
• Cost/token optimization and multi-model routing.
• Intuit experience or internal developer tools (CI/CD, Jira automation, developer portals).

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuitregistered: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.