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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer - **Company:** Intuit Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $202,500.0 - $274,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, BigQuery, Cloud Computing, Continuous Integration, Software Design Patterns, Distributed Systems, Java Virtual Machine (JVM), NoSQL, Object-Oriented Software Development, RabbitMQ, Data Streaming, Systems Integration, Software Technical Review, TypeScript, Google Cloud, System Availability, Large Language Models, Technical Debt, Kubernetes, Information Technology, Production Code, Apache Kafka, Graphql, Api Design, Amazon Simple Queue Service (SQS), Terraform, Grpc, Api Management, Docker, Web Api - **Published:** September 7, 2026 - **Apply:** https://dejobs.org/x/x/45565E5618674A9DABC00468EA03ACA0/job/ ## About the Role * 7+ years delivering enterprise-class applications, with a strong focus on backend software development, API design, and robust client/server contracts. * 5+ years designing complex distributed systems that operate at scale. * BS/MS in Computer Science, Engineering, or a related field, or equivalent practical experience. * Core languages: strong proficiency in TypeScript and/or Scala (or another functional/JVM language with demonstrated ability to ramp quickly - we code primarily in Scala and TypeScript). * APIs: deep experience designing and consuming web APIs, with hands-on GraphQL schema design and federation experience (REST and gRPC also relevant). * Architecture & infrastructure: expertise in scalable microservices architectures, messaging patterns, container orchestration (Kubernetes, Docker), and infrastructure-as-code (Terraform). * Event streaming & messaging: production experience with Kafka (or Pub/Sub, SQS, RabbitMQ) and the design of idempotent, exactly-once-effective, event-driven workflows. * Cloud: hands-on development in a public cloud environment - Google Cloud strongly preferred (GKE, Pub/Sub, BigQuery, Spanner/Cloud SQL). * Data: strong relational schema design, NoSQL, and high-volume low-latency data pipelining. * AI capability: proficient in - or highly capable of - integrating and evaluating AI in production, including LLM prompting, tool/function calling, and agentic development workflows; a high-level understanding of model types, their limitations, and how to measure accuracy. * Foundational excellence: solid grounding in OOP and functional design, algorithms, design patterns, test automation (TDD, unit/integration/functional), and CI/CD. * Technical leadership: a track record of setting direction, running design reviews, mentoring senior engineers, and serving as the cross-functional go-to person without relying on direct authority. * Communication: excellent written and verbal skills; able to explain complex technical topics clearly and persuasively to technical and non-technical audiences alike. ## Description * Own critical banking systems end-to-end. Drive significant technical initiatives across every layer of the stack - from data model and ledger design through GraphQL API contracts to the member-facing experience - for Checking, Savings, and money movement. * Architect for scale, correctness, and trust. Create robust, scalable, and secure technical designs for high-volume, low-latency financial systems, balancing short-term delivery against long-term architectural health, and ensuring high availability and optimal performance. * Stay hands-on. Spend roughly 60-70% of your time writing high-quality, performant, production code while setting the technical direction for your team. * Lead the event-driven backbone. Design and evolve Kafka-based messaging and event-streaming patterns that keep balances, transactions, notifications, and partner integrations consistent and idempotent at scale. * Drive AI-native innovation. Identify high-impact opportunities to apply AI and agentic capabilities - both in the product and in how we engineer - take AI-powered features to production, and evaluate their impact with the right metrics. Coach the team on using AI development tools effectively and responsibly. * Act as the technical subject-matter expert. Lead the design of complex features, run technical design reviews, and lead a small group of engineers through hard programming and design problems. * Lead technical execution. Own requirements gathering, technical design, project sequencing, and test planning; sequence complex dependencies and manage risk across multiple systems and teams. * Partner with bank and network partners. Work with our sponsor bank, processors, and payment network partners to integrate new capabilities and data, meeting the compliance, auditability, and regulatory obligations that come with holding member deposits. * Champion engineering quality. Set the bar on automated testing, CI/CD, observability, performance, security, and accessibility, and own quality through the full lifecycle - QA, pre-production, production, and post-release. * Elevate engineering talent. Provide clear goals, mentor senior engineers to the point where they lead initiatives independently, and give actionable feedback. * Solve systemic gaps. Partner with cross-functional leads and managers to systematically tackle technical debt, tooling deficiencies, and skill gaps that slow the team down. * Communicate with clarity. 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