Software Architect - Oracle Health

Oracle Oracle · Enterprise · United States

Software Architect role focused on Oracle Health Analytics, architecting and driving next-generation data-driven solutions. The role involves designing scalable platforms, developing AI-enabled innovations using LLMs and agentic architectures, and leading transformational change in health analytics.

What you'd actually do

  1. Architectural Leadership: Design and lead the development of scalable, high-performance data warehouse and analytics platforms that integrate legacy and modern systems.
  2. AI-Enabled Innovation: Develop and deploy solutions that leverage advanced AI, including LLMs (e.g., GPT-based models), agentic architectures, and deep research methodologies, to enhance data insights and automate complex analytics.
  3. Transformational Change: Challenge existing architectural assumptions and spearhead deep system transformations to support next-generation health analytics capabilities.
  4. Cross-Functional Collaboration: Partner with executive leadership, product teams, and external stakeholders to align technical strategy with business objectives, particularly in the health data space.
  5. Mentorship & Culture: Inspire and mentor engineering teams, fostering an environment of innovation, continuous learning, and technical excellence.

Skills

Required

  • 15+ years of experience delivering and operating large-scale, highly available distributed systems and data analytics platforms.
  • Exceptional expertise in data warehouse technologies and analytics, with a proven track record working with platforms such as Databricks and Snowflake.
  • Deep experience integrating AI and advanced analytics into data warehouses—developing solutions that utilize LLMs (e.g., GPT, Claude), agentic architectures, and other deep research frameworks to push the boundaries of traditional data paradigms.
  • Strong proficiency in SQL, Python, Java (or equivalent), coupled with a solid grounding in data structures, algorithms, and distributed computing fundamentals.
  • Proven ability to architect and implement complex integrations across legacy and modern analytics systems, ensuring data integrity and performance at scale.
  • Excellent communication skills, technical acumen, and a strong product sense—able to navigate both business and technical landscapes.

Nice to have

  • A Bachelor’s degree in Engineering, Computer Science, or a related field is required; an advanced degree is a plus.

What the JD emphasized

  • AI-Enabled Innovation
  • agentic architectures
  • deep research methodologies
  • integrating AI and advanced analytics into data warehouses
  • agentic architectures
  • deep research frameworks

Other signals

  • Develop and deploy solutions that leverage advanced AI, including LLMs (e.g., GPT-based models), agentic architectures, and deep research methodologies
  • Deep experience integrating AI and advanced analytics into data warehouses—developing solutions that utilize LLMs (e.g., GPT, Claude), agentic architectures, and other deep research frameworks