Staff Software Engineer

QuickBooks, Intuit’s flagship accounting software, supports millions of small business owners and accountants worldwide through various offerings, including QuickBooks Online, Desktop, and mobile editions. The Business Platforms provides essential features like Core Accounting, QuickBooks Commerce, IAS and expert solutions. By utilizing cutting-edge technologies and adhering to Global Engineering Principles, the Business Platforms product development team fosters innovation to deliver an exceptional user experience.

Intuit’s Business Platform (BP) is seeking a Staff Software Engineer to enhance the Business Platforms Data Engineering team. This team is responsible for vital data platforms supporting Intuit’s Small Business products, such as QuickBooks Accounting , Intuit Experts and Intuit Accountant Suite. You will play a critical role in shaping the data strategy and delivery, utilizing your expertise in cloud platforms, big data technologies, and AI to solve complex data challenges while aligning infrastructure with business objectives.

Your contributions will span the entire product lifecycle, allowing you to design, develop, and optimize Intuit’s data solutions. You will enhance onboarding experiences, remove entry barriers, and ensure scalability and efficiency of data solutions. At Intuit, we prioritize nurturing talented technologists passionate about solving customer problems, demanding innovation to create highly interactive applications capable of handling petabytes of data.

Join us in driving prosperity for small businesses globally.

Responsibilities

• Drives velocity in the organization by accelerating customer, business, and technology outcomes by identifying and driving key opportunities across the company.

• Understands customer behaviors and partners with cross-functional partners to influence and drive end-to-end solutions for customer problems.

• Executes with a boundaryless mindset and contributes to solutions outside of their primary area of ownership.

• Develop, design, and implement robust, high-performance data pipelines—both batch and real-time—along with scalable data platforms on AWS Cloud. Ensure reliability and scalability while maintaining comprehensive test coverage to deliver seamless and efficient data processing solutions.

• Knowledge of building AI native applications

  • Guides the applicability of AI to customer problems through a deep understanding of the application, best practices, but also the limitations of AI technologies.
  • Demonstrated ability to embrace the rapid evolution of the AI space as part of the development process.
  • Understands evaluation tools to validate and measure the accuracy of solutions.
  • High-level understanding of how traditional AI + genAI models work, the different types of AI models that exist, and their pros and cons.
  • Understanding of the latest tools and technologies that apply AI to real-world applications.

• Research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership best practices.

• Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data architectures.

• Team/ Collaboration:

  • Collaborate with cross-functional teams, including product teams, AI and Data Science teams, Data Platforms, and DevOps teams, to align data engineering strategies with enterprise goals.
  • Be seen as a key innovation and thought leader in the AI and Data space, able to recommend and promote both platform and process improvements within Intuit’s AI and Data infrastructure, in order to lift the entire organization.
  • Works with cross-functional team members from Architecture, Product Management, and Operations to design, develop, test, and release features
  • Optimization: Look for opportunities to drive step-changes in performance and cost reduction, through new platforms or tuning of existing platforms.

Qualifications

Qualifications

• BS or MS in Computer Science, Data Engineering, or a related field.

• 8+ years of experience in software engineering or Data engineering

• Expertise in developing Data Modelling, Data warehousing, Data pipelines development using frameworks like Apache Spark, Hadoop, and streaming technologies such as Kafka.

• Familiarity with data models, data structures, and schema management.

• Understanding of both streaming (e.g., Kafka) and batch data processing constructs.

• Expertise in Realtime data analytics using Apache Kafka is highly desirable.

• Strong background using cloud platforms such as AWS, Azure, or GCP, including Amazon Web Services: EC2, S3, EMR (Elastic Map Reduce), RedShift, DynamoDB, and Athena, or equivalent cloud computing approaches. Expertise with AWS is specifically a must-have

• Proven ability in designing, building, and shipping complex, data-intensive, and scalable systems in a real-world setting.

• Experience with Big-Data Technologies and low-latency NoSQL datastores (Hive, HBase, Spark, Kafka, Storm, MapReduce, HDFS, Splunk, Zookeeper, MemSQL, Cassandra, Redshift, GraphDB), understands the concepts and technology ecosystem around both real-time and batch processing in Hadoop

• Hands-on experience with Generative AI models (LLMs, diffusion models), frameworks (LangChain, Hugging Face, OpenAI/Anthropic APIs), and RAG implementations.

• Hands-on experience preferred in developing and deploying applications written in Java/Kotlin/Python and PostgresSQL/OpenSearch, to reduce impedance mismatch when collaborating with partner teams.

• Knowledge of MLOps/LLMOps practices and CI/CD pipelines for AI workloads (e.g., MLflow, Kubeflow, LangSmith).

• Demonstrable experience deploying and managing Large Language Models (LLMs) based Applications in production environments

• Hands-on programming experience using Java or Python

• Ability to work effectively in a fast-paced, collaborative, and innovative environment, understanding organizational dynamics and decision pathways.

• Strong understanding of Agentic AI systems with proven ability to design and implement production-grade solutions.

• Drive alignment between enterprise architecture and business needs.

• Conduct quick proof-of-concepts (POCs) for feasibility studies and take them to the production

• Lead by example, demonstrating best practices for unit testing, test automation, CI/CD performance testing, capacity planning, documentation, monitoring, alerting, and incident response

• Effective listening skills and strong collaboration to lead change by example and through influence

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.