Job
Description
As a Principal Software Engineer, you should be proficient in Data Structures and Algorithms, Java, object-oriented principles, building distributed systems, vector databases, containerization, orchestration, and cloud-native architectures. You will collaborate with cross-functional teams to build scalable, reliable, and production-ready solutions. Oracle is investing heavily in Generative AI, and as a Principal Software Engineer, you must have a good understanding and experience in leveraging the capabilities of Large Language Models. In this role, you will design, develop, and build scalable services that leverage the latest and greatest advancements in GenAI to solve complex business problems intelligently. Your expertise will be pivotal in developing Conversational AI solutions, Agentic flows using LLM and other cutting-edge Machine learning techniques to shape up and enhance users' experience with AI/ML/GenAI capabilities. You will also partner with product managers, software engineers, and operation teams to leverage engineering innovations to simplify the business requirements into scalable solutions. The ideal candidate is highly technical, proficient in Java, Python, Data Structures, Algorithms, Kubernetes, Agentic frameworks (LangGraph, Autogen, AG2, Agent Development Kit) and has experience in building scalable solutions particularly around ML and AI/GenAI/Agentic Workflows, but can lead across the full stack, along with good product sense and business understanding, to map the technology choices to the context of each initiative. Write elegant and performant code in Java. Create detailed technical designs specifications, present it to the team and write code as per the design. Perform thorough peer code reviews. Design and build scalable solutions for distributed systems using microservices. Develop proof of concepts in Java as well as python for AI and GenAI solutions. Design and build high-quality, scalable, and efficient software solutions that brings GenAI capabilities, leveraging latest advancements such as Agentic LLM and RAG frameworks, etc. in GenAI space. Lead the incubation of new initiatives, architect scalable solutions, and drive strategic technology choices to develop and deliver AI/ML capabilities in a micoservcies architecture for our customers. Leverage third-party and in-house ML tools & OCI platform to develop reusable, highly performant machine learning systems with low latency serving and reliable means to update/re-train ML models. Design, test, and deploy Machine learning models, including large-language models and build pipelines at scale for batch and real-time use cases. Work collaboratively with cross-functional partners including product managers, operations team, and data scientists. Communicate continually with the project teams and explain progress on the development effort. Ensures quality of work through development standards and QA procedures. Keen on improvising technical solutions and processes emphasizing discovery through doing, iteration, and feedback loops. Identify opportunities for business impact, understand and prioritize requirements for machine learning systems and data pipelines, drive engineering decisions, and quantify impact.
