Responsibilities
- Design, develop, and implement robust batch and real-time data pipelines and scalable AWS data platforms.
- Improve the reliability, scalability, performance, and cost efficiency of data solutions handling large-scale data.
- Drive end-to-end solutions for customer and business problems in collaboration with cross-functional teams.
- Guide the applicability of traditional AI and generative AI to customer problems and evaluate solution accuracy.
- Design, implement, and deploy production-grade AI-native, agentic, and LLM-based applications.
- Research emerging data and AI technologies and contribute to enterprise architecture, strategy, and thought leadership.
- Collaborate with product, architecture, AI, data science, data platform, DevOps, and operations teams.
- Conduct proof-of-concepts and take feasible solutions into production.
- Lead by example in unit testing, test automation, performance testing, capacity planning, monitoring, alerting, documentation, and incident response.
Requirements
- BS or MS in Computer Science, Data Engineering, or a related field.
- 8+ years of experience in software engineering or data engineering.
- Expertise in data modeling, data warehousing, data pipeline development, Apache Spark, Hadoop, and streaming technologies such as Kafka.
- Strong understanding of data models, data structures, schema management, and batch and streaming processing.
- Expertise with AWS is required, including experience with cloud platforms and services such as EC2, S3, EMR, Redshift, DynamoDB, and Athena.
- Experience with big data technologies and low-latency NoSQL data stores, including Hive, HBase, Spark, Kafka, Storm, MapReduce, HDFS, Splunk, Zookeeper, MemSQL, Cassandra, Redshift, and GraphDB.
- Proven ability to design, build, and ship complex, scalable, data-intensive systems.
- Hands-on experience with generative AI models, LLMs, diffusion models, LangChain, Hugging Face, OpenAI or Anthropic APIs, and RAG implementations.
- Experience deploying and managing LLM-based applications in production and designing production-grade agentic AI systems.
- Preferred experience developing and deploying applications with Java, Kotlin, Python, PostgreSQL, and OpenSearch.
- Knowledge of MLOps and LLMOps practices and AI workload tooling such as MLflow, Kubeflow, and LangSmith.
- Hands-on programming experience with Java or Python.
- Ability to lead through influence, collaborate effectively, navigate organizational dynamics, and align enterprise architecture with business needs.
Benefits
- Competitive compensation package with pay-for-performance rewards.
- Position may be eligible for a cash bonus, equity rewards, and benefits under applicable plans and programs.
- Pay is based on job-related knowledge, skills, experience, and work location.
Tech Stack
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.