Headline

AI Engineer at Oracle | MLOps · Generative AI · LLMs · RAG · AI Agents | Data Platform Engineering

About

I'm an AI engineer with 3.5+ years at Oracle, specialising in Generative AI, LLM applications and the data platforms that power them. My core strength is building production AI systems end to end: RAG pipelines, AI agents with tool calling, retrieval with hybrid search, embeddings and reranking, prompt engineering, and evaluation. I focus on making AI reliable in real use, not just impressive in a demo. I bring a strong data-engineering foundation to that work. I'm hands-on with Apache Spark (PySpark), Apache Iceberg, Kafka and large-scale data pipelines, and I care about the parts that keep systems trustworthy in production: testing, observability, data quality and CI/CD. On the cloud side, I work across Oracle Cloud Infrastructure and GCP, with Docker and Kubernetes for deployment, and I'm comfortable owning a system from architecture through to production.

Location

India

AI stack

claude code

hugging face

langchain

langfuse

langgraph

mcp

Work experience

Data Scientist 2 at Oracle, Mar 2026 - Present · 8 mos, Part of the platform engineering team that modernised Oracle's enterprise data platform into an Apache Iceberg agentic lakehouse on OCI, working where generative AI meets large-scale data engineering. • Agentic AI for operations: Built LLM-powered agents that automate platform troubleshooting and diagnose failures, reducing manual effort for engineering and on-call teams. • Natural-language data access: Developed AI-driven interfaces that let users query and explore lakehouse data in plain English, grounded in governed enterprise metadata. • Retrieval and grounding: Applied RAG, embeddings, hybrid search and reranking to make AI outputs accurate and reliable in production. • Observability and reliability: Engineered observability, data validation and data-quality tooling for streaming and batch pipelines, supporting the platform's automated incident response. • Lakehouse data engineering: Build and operate large-scale data pipelines with Apache Spark (PySpark), Apache Iceberg and Kafka across multiple enterprise data sources. • Engineering excellence: Established automated testing and CI/CD practices that keep platform releases safe, reproducible and fast. • MLOps and observability: Implemented LLM observability with Langfuse, tracing agent workflows and monitoring prompts, responses, latency and cost to keep AI systems reliable and continuously improving in production.

Consultant (AI and Cloud) at Oracle, Jun 2023 - Mar 2026 · 2 yrs 10 mos, Delivered large-scale cloud deployments, automation and GenAI tooling for tier-1 enterprise telecom customers. • Cloud deployment and integration: Drove application deployment and systems integration on large private cloud environments for mission-critical telecom networks. • Zero-downtime migrations: Migrated live customer workloads and enterprise databases from bare-metal to cloud with no service disruption. • Automation: Built Python and Shell tooling to automate monitoring and routine operations, significantly reducing manual effort for the team. • Monitoring and event processing: Designed high-throughput monitoring and alerting pipelines using Kafka, Python and Grafana for real-time network visibility. • GenAI innovation: Built GenAI tools on OCI Generative AI and vector search to automate internal engineering work and improve team productivity. • Production quality: Debugged and validated software in live production environments, finding and resolving critical issues while working closely with development, QA, support and consulting teams.

Project Intern at Oracle, Jan 2023 - Jun 2023 · 6 mos, Worked on cloud-native telecom deployments and automation for enterprise network applications. • Migration automation: Built Python automations to migrate non-Oracle cloud network applications into Oracle formats, reducing manual conversion effort and speeding up onboarding. • Cloud-native deployment: Deployed and configured 5G network functions built on microservices, Docker and Kubernetes. • Cloud integration: Prepared systems and network applications for cloud integration across customer environments. • Monitoring: Monitored system health and performance with Prometheus and Kibana.

Software Developer at Indianhempstore.com, Jun 2022 - Dec 2022 · 7 mos, Dehradun, Uttarakhand, India, Developed the company's multi-vendor e-commerce platform end to end, working directly with customers, vendors and the internal team. • Platform development: Built and launched a complete multi-vendor (B2B and B2C) e-commerce platform, covering vendor onboarding, product catalogues, orders and payments. • Customisation and integrations: Developed extensive custom features and integrated third-party APIs to fit the business's specific workflows. • Performance and SEO: Improved site performance and search visibility, helping grow organic traffic. • Stakeholder collaboration: Worked closely with customers, vendors and teammates to gather requirements, resolve issues and turn feedback into product improvements.

Education

Bachelor of Technology, Computer Science Specialized in AI ML, University of Petroleum & Energy Studies

Public links

github: https://github.com/aravinds44

aravindsaji.com: https://aravindsaji.com/