Intuit · KA, India
Skills: React, Python, Java, GraphQL, CI/CD
Overview ------------
ARP evaluates whether internal platforms are “agentic-ready” for end-to-end AI agent development. Its evaluation engine normalizes top use cases, spawns agents in virtualized environments, executes their plans, automatically files issues for friction points (such as missing docs or APIs), and re-runs checks on every CI/CD deploy to prevent regressions. This role sits on the Core Platform Framework team, which builds the evaluation platform and seeks research-minded engineers focused on agent orchestration and LLM tooling, distinct from the Operations/Adoption team.
Responsibilities
Core platform architecture: build and evolve the virtualization/harness layer, the agent plan-then-execute engine, and the friction detection and auto-ticketing pipeline. Model orchestration and cost efficiency: implement dynamic, step-level orchestration, replacing single static models, that routes tasks to cost-effective models (open-source and Claude), tracking cost and performance per step. Telemetry and auditability: build scalable logging, cost and telemetry systems so every agent run is fully auditable and cost-accountable. Use-case normalization: contribute to technical standards that make use cases agent-readable across differently documented capability platforms. Cross-team collaboration: partner with capability, operations and adjacent platform teams on friction reporting, PRD-to-action pipelines, RAG-backed architecture context and OPA policy validation. Roadmap leadership: help deliver the roadmap from foundational tooling (plugins, RBAC, alerting) to automation (auto-fix agents, continuous re-runs) and governance visibility. Mentorship and standards: mentor junior engineers and contribute to engineering standards through design reviews, architecture documentation and hands-on contributions.
Qualifications
7+ years of software engineering experience, focused on distributed systems or developer platforms. Hands-on experience building or operating LLM-agent sys…
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