Key Responsibilities
LLM Application Engineering
- Architect and implement scalable LLM-driven applications, leveraging advanced prompt engineering, model customization, and inference optimization.
- Design agentic solutions managing intent routing and workflow orchestration using frameworks such as LangGraph.
- Develop and optimize Retrieval Augmented Generation (RAG) systems, including chunking, embedding selection, vector indexing, and ranking.
- Drive robust prompting patterns for function calling, considering cost, latency, and accuracy trade-offs.
- Integrate with secure microservices, enforce data schemas and metadata lineage, and connect with MCP-compatible tools.
- Implement evaluation datasets, automate regression testing, and monitor quality, cost, and safety of deployed AI systems.
- Establish guardrails for Responsible AI, such as PII handling, access control, and policy enforcement.
Machine Learning & Applied AI Science
- Design, train, and deploy machine learning models develop end-to-end ML pipelines.
- Monitor and optimize model performance, detect data drift, and retrain models as needed.
- Champion best practices in data acquisition, feature engineering, and model curation.
- Lead proof-of-concept AI experiments and publish best practices for the organization.
LLMOps & Platform Engineering
- Manage versioning for prompts, models, and pipelines oversee A/B testing and rollouts.
- Instrument tracing, telemetry, and robust exception handling for agentic workflows.
- Steer integration and interoperability with Oracle Fusion products and cloud infrastructure.
Evaluation & Quality
- Develop and maintain rigorous evaluation frameworks, key performance indicators, and benchmarking strategies for model performance, safety, and business value alignment.
Responsible AI & Security
- Serve as a technical authority to ensure privacy, model governance, Responsible AI, and operational security throughout the ML lifecycle.
Conversational UX & Domain Leadership
- Define standards and mentor engineers for multi-turn dialog systems and conversational interfaces.
- Act as a domain expert, influencing technical direction, reviewing code, and fostering a culture of innovation and knowledge sharing in agile teams.
Essential Skills
- Advanced expertise in Python (and/or Java) and modern ML/AI libraries (TensorFlow, PyTorch, etc.).
- Deep experience with large language models (OpenAI, Google, proprietary/foundation models), prompt engineering, and custom model deployment.
- Mastery of cloud enterprise ecosystems (with Oracle Cloud and Fusion preferable) strong grasp of enterprise-class observability, governance, and security.
- Demonstrated skills in architecting scalable AI/ML pipelines and deploying production-ready enterprise applications.
- Strong background in conversational AI and NLP, including dialog management and customer-centric natural language experiences.
- Proven ability to enforce best practices in responsible, safe, and secure AI development.
- Exceptional leadership, mentoring, and technical communication skills.
- Track record of influencing technical direction and driving adoption of advanced AI techniques in multidisciplinary teams.
Qualifications
Required:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative discipline
- 8+ years of industry experience in software or AI/ML development, including at least 3 years in LLMs or deep learning.
- Demonstrable experience with modern AI/ML frameworks and deploying models in cloud production environments.
- Experience with enterprise-level data pipelines, versioning, CI/CD, and ML/MLOps tooling (e.g., OCI Data Science, Kubeflow, MLflow).
- Hands-on expertise integrating AI with microservices, enterprise APIs, and secure data architectures.
- Deep understanding of Responsible AI principles, privacy, and model governance.
Preferred:
- Experience with Oracle Cloud Infrastructure (OCI) and Oracle Fusion applications.
- Prior design and implementation of agentic workflows and Retrieval Augmented Generation (RAG) systems.
- Strong publication record, patents, or industry contributions in applied AI.
- Experience with productionizing multi-turn conversational UX and building enterprise AI solutions at scale.
- Active participation in AI/ML research or open-source communities.
Why Join Our Team
- Shape the future of Oracle's AI solutions driving global business value.
- Work on impactful, immediate solutions incorporated into Oracle's product suite.
- Lead transformative, complex AI initiatives in a highly supportive and innovative environment.
- Collaborate with top AI engineers and scientists in a culture that encourages continuous learning and growth.
As a member of the software engineering division, you will take an active role in the definition and evolution of standard practices and procedures. You will be responsible for defining and developing software for tasks associated with the developing, designing and debugging of software applications or operating systems.
Career Level - IC4
