Senior AI Software Engineer

About the role

Oracle MADC is seeking a Senior AI Software Engineer to embed AI capabilities into its product portfolio. The role demands strong coding expertise, sound technical judgment, and the ability to lead engineering initiatives from design through delivery.

Key responsibilities

• Design, develop, and maintain production‑grade software for AI‑enabled Oracle products.
• Build scalable services, APIs, SDKs, and reusable platform components.
• Navigate large codebases, quickly grasp existing architectures, patterns, and dependencies.
• Translate product and business requirements into practical technical designs and implementation plans.
• Integrate modern AI and Large Language Model (LLM) capabilities into reliable enterprise systems.
• Improve system quality across reliability, performance, maintainability, testing, and operational readiness.
• Review technical designs and code changes with a focus on correctness and long‑term impact.
• Lead sprint execution, including planning, prioritization, task breakdown, and delivery tracking.
• Mentor engineers and raise engineering standards across the team.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• Significant professional experience in backend, platform, infrastructure, or enterprise product development.
• Proficiency in one or more programming languages such as Java, Python, or C++.
• Strong understanding of data structures, algorithms, system design, and software architecture.
• Experience building production‑grade services, APIs, SDKs, libraries, or platform components.
• Working knowledge of modern AI systems, Large Language Models, and AI application development.
• Experience with testing, debugging, performance analysis, CI/CD, and production support.
• Demonstrated technical leadership through code reviews, design reviews, mentoring, and engineering planning.

Required skills

• Java
• Python
• C++
• Data structures and algorithms
• System design and software architecture
• Production‑grade services, APIs, SDKs, libraries
• Modern AI systems and Large Language Models
• AI application development and platform integration
• Testing, debugging, performance analysis
• CI/CD pipelines
• Production support practices
• Distributed systems
• Cloud services
• Large‑scale backend platforms
• Developer‑facing tools