Senior AI Application Engineer

Role Overview: You will be responsible for designing, developing, troubleshooting, and debugging software programs for databases, applications, tools, and networks. You will have the opportunity to work with cutting-edge technologies in an enterprise environment and contribute to the development of scalable microservices and AI-powered capabilities. Key Responsibilities: - Design and develop cloud-native application services on Kubernetes using Java, Python, and Spring Boot. - Integrate application components with Oracle Cloud Infrastructure (OCI) services, including GenAI Service, Object Storage, and API Gateway. - Implement AI-powered capabilities using Large Language Models (LLMs), prompt engineering, and agentic frameworks such as OpenAI Agent SDK or LangGraph. - Build Retrieval-Augmented Generation (RAG) workflows including embeddings, indexing, and hybrid search. - Support CI/CD processes and containerized deployment workflows using Podman, Docker, and Oracle Kubernetes Engine (OKE). - Troubleshoot application and runtime issues across distributed environments. - Work with cross-functional engineering teams to align solution designs with business requirements. - Conduct independent research on emerging AI technologies, tools, and engineering patterns to introduce improvements and new solution approaches. - Share knowledge, mentor peers, and contribute to internal enablement of AI and cloud development best practices. Qualification Required: - Bachelors or Masters degree in Computer Science, Engineering, or related technical field. - Minimum 3+ years hands-on experience in software development using Java, Python, Spring Boot, with strong grounding in data structures, algorithms, and their application in solving complex engineering challenges. - Experience in designing scalable microservices in an enterprise environment. - Practical exposure to working with Large Language Models (LLMs) and agentic frameworks. - Experience with Oracle Cloud Infrastructure (OCI) services and container technologies. - Strong communication skills and the ability to collaborate across distributed teams. - Proven ability to drive technical outcomes, take ownership of deliverables, and work independently in fast-evolving AI solution spaces. - Demonstrated problem-solving ability when working with complex AI workloads, distributed systems, and cloud-native application behaviors. - A proactive, experimentation-oriented mindset with a strong willingness to learn emerging AI technologies, frameworks, and engineering patterns.,