Senior Staff Engineer — Intuit Agent Ready Platform, PDX

Job description

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.

Qualifications

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.

Preferred

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 Intuit®: 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 compariso ns across categories of ethnicity and gender.