Senior Software Engineer - AI Builder
Pathfinder is Intuit's intent-based AI test automation platform - natural-language prompts executed by autonomous agents against live applications, with 1M+ E2E runs recorded and 18+ teams building on it across TurboTax and beyond. We're moving from a proven platform into the next phase: PRD-to-test generation, Figma-to-test generation, and full SDLC integration for auto-generated tests. This is greenfield problem space, not a known pattern with reference implementations to lean on.
We're looking for a Senior Software Engineer to own the layer that determines whether Pathfinder scales: multi-agent execution orchestration and cross-platform execution caching. This is the kind of person who treats an LLM rate limit not as a blocker to escalate but as a system design problem to solve - someone fluent in building with AI, not just building AI features, who can reason about agentic execution patterns, cost/performance tradeoffs, and orchestration architecture with no existing playbook to reference. You'll be hands-on 80-90% of the time, architecting and shipping the infrastructure that lets autonomous agents run reliably at scale, while setting technical direction for a small team solving problems nobody has solved before.
This role suits a builder - someone who prototypes fast, is comfortable being wrong in week one and right by week three, and treats ambiguity as the interesting part of the job rather than a reason to wait for more clarity.
Responsibilities
- Design and build the multi-agent execution orchestration and cross-platform execution-caching infrastructure that Pathfinder's scale and LLM cost efficiency depend on
- Drive significant technical initiatives end-to-end, from functional requirements through technical specification, test planning, and production rollout
- Act as the technical subject matter expert on agentic execution systems - lead a small team through hard, unprecedented programming and design problems
- Prototype and validate proofs of concept quickly; use AI-assisted development tools fluently as part of your own workflow, not just as a subject you build for
- Generate technical documentation that communicates architectural and design tradeoffs clearly to both engineering teams and business stakeholders
- Resolve defects across QA, pre-production, production, and post-release patches for a system running 1M+ E2E test executions
- Work cross-functionally with product management, QA/QE, and partner teams (18+ teams currently building on Pathfinder) to unblock their adoption and surface platform gaps early
- Operate in Agile/Scrum cadences while retaining the independent judgment to make calls the backlog hasn't anticipated yet
Qualifications
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience; 3+ years building cloud-based platforms or services
- 3+ years developing systems/software for large-scale environments (Java, Springboot), with demonstrated ability to design for scale quickly rather than needing a decade to build the instinct
- Hands-on experience building with AI: you've shipped something using LLM APIs, agentic frameworks, or AI-assisted coding tools as a core part of the system, not as an add-on. Comfortable reasoning about prompt-driven execution, model behavior under load, and the failure modes that come with non-deterministic systems
- Fluent daily user of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) - this role expects you to build faster because of AI, and to bring that instinct to designing infrastructure where AI agents are the primary actor
- Practical experience with microservices and messaging technologies (REST, GraphQL, Kubernetes, Kafka, ActiveMQ) and database design across SQL (MySQL) and NoSQL (DynamoDB, Cassandra)
- Some exposure to the cost/performance mechanics of running LLMs in production - rate limits, token economics, caching strategies, orchestration patterns - is a strong plus even without years of tenure in the space, since almost nobody has years of tenure here yet
- Strong CS fundamentals: data structures, algorithms, and system design intuition that holds up with no reference architecture to copy
- Working knowledge of TDD and SDLC practices, with the judgment to know when rigor matters and when speed does
- A builder's bias toward shipping working prototypes over long design docs, balanced with the discipline to document architecture decisions clearly once validated
- Self-starter who makes decisions independently in ambiguous, fast-moving conditions, and communicates clearly across technical and non-technical audiences
- Comfortable working across global teams and time zones in a fast-paced, high-adaptability environment
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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 comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
