1 day ago
Base Salary
$203k - $274k/yr
Responsibilities
- Own the architecture of high-volume, highly available distributed services with strict correctness, reliability, and latency requirements.
- Design event-driven and workflow-based architectures using messaging, state machines, and sagas.
- Lead capacity planning, performance tuning, multi-region resiliency, graceful degradation, load shedding, observability, SLOs, alerting, and incident prevention.
- Design and ship agentic workflows that automate complex multi-step customer and operations tasks.
- Build secure tool and API layers, including MCP servers and tool-calling interfaces, for LLM-based assistants.
- Define authorization, human-in-the-loop checkpoints, policy enforcement, auditability, and other agent guardrails for sensitive data.
- Establish evaluation, testing, and monitoring practices for LLM and agent behavior, including offline evaluations, golden datasets, regression suites, and production metrics.
- Partner with data science to bring prediction, anomaly detection, personalization, and other ML capabilities into production.
- Lead requirements, technical specifications, test planning, estimation, risk identification, and trade-off communication for major initiatives.
- Spend approximately 60–80% of the role designing, coding, and reviewing; mentor engineers and serve as the technical go-to person for complex cross-system issues.
Requirements
- BS/MS in Computer Science or equivalent work experience.
- 8+ years of experience building systems and services for large-scale business environments, including Java and Spring Boot.
- 5+ years designing, building, and operating robust, highly scalable, highly available distributed systems.
- Strong knowledge of consistency models, idempotency, concurrency, partitioning, caching, and failure handling.
- Practical experience with microservices and messaging technologies including REST, GraphQL, Kafka, Kubernetes, and AWS.
- Strong database design experience with SQL and NoSQL systems including MySQL, PostgreSQL, DynamoDB, and Cassandra.
- Hands-on experience building and shipping AI/ML-powered features and LLM-based applications to production, including prompting, RAG, and tool or function calling.
- Experience designing agentic systems with multi-step workflows, tool and API integration, orchestration, and guardrails.
- Experience evaluating AI systems in production through evaluation design, quality and safety metrics, and iteration on model and agent behavior.
- Expertise in data structures, algorithms, software design, and architecture.
- Strong leadership and communication skills, including leading design reviews and explaining complex technical issues to technical and non-technical audiences.
- Preferred experience in fintech, payments, compliance-sensitive domains, operational AI-agent workflows, or workflow engines such as Temporal and Step Functions.
- Full-stack experience with React and JavaScript is a plus.
Benefits
- Competitive compensation package with pay-for-performance rewards.
- May be eligible for a cash bonus, equity rewards, and benefits according to applicable plans and programs.
- Expected base pay range is $202,500–$274,000 for Mountain View.
Tech Stack
Amazon DynamoDBApache CassandraApache KafkaAWSGraphQLJavaJavaScriptKubernetesMySQLPostgreSQLReactSpring Boot
Categories
About Intuit
Intuit is a global technology platform that helps our customers and communities overcome their most important financial challenges. Serving millions of customers worldwide with TurboTax, QuickBooks, Credit Karma and Mailchimp, we believe that everyone should have the opportunity to prosper and we work tirelessly to find new, innovative ways to deliver on this belief. We encourage conversations on this page and will not delete comments that follow our terms of use. In order to keep this a safe community, the below posts may be removed: Repeated posts of the same content, spam or posts from fake accounts or profiles, offensive language or material, threats to others in the community, posts deliberately aimed to have a negative effect on the community or conversations.