We’re looking for an AI Developer to help shape the future of AI at Oracle. The ideal candidate has a strong foundation in data science and applied machine learning, with practical exposure to building agentic workflows (., RAG, NL-to-SQL, microservices). You will collaborate with product, engineering, data, and security teams to deliver reliable, compliant, and scalable AI capabilities. You take ownership of features and services, make thoughtful trade-offs, and contribute to engineering excellence.
What You’ll Do :
Build AI-Powered Applications
- Design and implement features in AI-driven applications, primarily using Python or similar languages.
- Partner with cross-functional teams to deliver reliable, scalable solutions.
Data, Experimentation, and Evaluation
Execute data preparation (feature selection, ETL, data quality) and contribute to robust evaluation frameworks.Run experiments, analyze results using appropriate metrics, and iterate to improve performance and reliability.MLOps and LLMs
Contribute to model deployment, monitoring, versioning, and guardrails for safety and reliability.Design and implement agentic workflows using frameworks like LangGraph (or similar), including grounding with RAG and tool use.Responsible AI and Compliance
Apply privacy-by-design and secure coding practices; partner with security and compliance teams as needed.Oracle Fusion and Conversational UX
Integrate AI features into Oracle business applications.Contribute to intuitive, user-centric conversational interfaces.Qualifications required :
Degree (or equivalent experience) in Computer Science, Engineering, Mathematics, Physics, Statistics, or related field.Proficiency with at least one programming language—Python preferred.Hands-on experience with ML libraries (., Scikit-learn, TensorFlow, PyTorch).Experience with cloud platforms, ideally OCI (also valued : AWS, GCP, Azure).Understanding of software engineering fundamentals, data structures, algorithms, and secure SDLC practices.Strong communication skills; effective collaboration across product, engineering, and security / compliance stakeholders.Demonstrated contribution to production ML / LLM systems (., services, pipelines, or features in production).Optional Architecture & Design Skills (Preferred) :
Working knowledge of software architecture fundamentals and system design patterns (., microservices).Practical experience modeling with UML and / or the C4 model; ability to produce sequence, class, and deployment diagrams that stay in sync with code.Familiarity with DDD techniques : identifying bounded contexts, strategic design, event storming, aggregate design, and context mapping.API and integration design : RESTful standards, gRPC, GraphQL, API gateways, schema versioning, and backward compatibility strategies.Event-driven architecture : experience with messaging systems (., Kafka) and reliable event processing basics (ordering, retries, idempotency).Data and storage design : relational vs. NoSQL trade-offs, indexing, caching strategies, and clear data contracts.Data governance : handling sensitive data with appropriate classification, retention, lineage, consent, and access controls aligned to privacy / compliance policies.Observability : designing for metrics, logging, tracing; SLOs, error budgets, and performance profiling.Security-by-design : basic threat modeling, secure defaults, secrets management, dependency scanning, and secure SDLC practices.Architecture documentation tools familiarity (., PlantUML, Mermaid, .Exposure to cloud-native architecture on OCI (preferred) or AWS / GCP / Azure : networking, IAM, container orchestration, service meshes, and managed AI / ML services.Optional Nice to Have :
Led or contributed to architecture spikes / prototypes and translated findings into solution patterns or reference implementations.Participation in design reviews or architecture forums; ability to articulate trade-offs to technical and non-technical audiences.Relevant certifications or coursework (., OCI Architect, systems design, software architecture).Career Level - IC3