Job Abstract

The Background

Oracle’s Fusion Applications group is designing and building the next-gen deployment platform for its suite of software products. We focus on transforming how Software Developers and DevOps engineers build cloud applications for enterprise customers. Our team is building new ML-powered services to improve developer productivity and automate the process of running cloud services. We will build RAG-powered applications to surface the right information at the right time, and agent-powered runbooks to automatically diagnose and remediate service issues

You are the builder here. You will be part of a team of intelligent, motivated, and diverse people and given the autonomy and support to do your best work using modern backend technologies, including LangChain, open-source LLMs, Kubernetes, Terraform, and more.

Our core values are our foundation and how we deliver excellence. We strive for equity, inclusion, and respect for all. We are committed to the greater good in our products and our actions. We are constantly learning and taking opportunities to grow our careers and ourselves. We challenge each other to stretch beyond our past to build our future.

Our team is fully remote. We currently have members spread across the US, India and Europe. We practice scrum and leverage Slack and Zoom heavily for day-to-day communication.

The Role

As a lead software engineer, you will be responsible for all stages of the software development lifecycle, from requirements gathering to coding, testing, CI/CD, and operational support. A successful candidate will bring a strong focus on our customers, a passion for innovative products, as well as hands-on experience as a software engineer applying the latest AI technologies.

Ideal Qualifications:

• Bachelor’s or Master’s degree in Computer Science or equivalent related field experience
• Strong software engineering skills
• Experience in leading the design and implementation of AI-powered services and applications and data pipelines.
• Hands-on experience with emerging LLM frameworks such as LangChain, LlamaIndex, vector stores, embedding models and instruction/chat models.