Principal Research Engineer - Agentic AI at Oracle Risk Management Services

, , United States -

Full Time

Start Date

Immediate

Expiry Date

16 Mar, 26

Salary

0.0

Posted On

16 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI, Generative AI, Machine Learning, Optimization, Agent Planning, Reasoning, Multi-Step Reasoning, Hierarchical Planning, Tool Routing, Memory Management, Verification, Tree Search, Graph Search, Python, PyTorch, JAX, Transformers

Industry

IT Services and IT Consulting

Description

At Oracle Analytics, we are building the next generation of enterprise AI products to enable intelligent data analysis at scale. Leveraging our foundational strengths in data management and enterprise software applications, we are advancing our platforms and applications by deeply embedding cutting-edge agentic AI, generative AI, and innovations in machine learning and optimization. Our AI and Applied Science team is seeking a highly motivated Principal Research Engineer to perform innovation in agent planning, reasoning, and the efficient implementation of multi-step reasoning agents across Oracle’s AI Data platform and intelligent applications. In this role, you will research, architect, and prototype nextgeneration agent planning and orchestration techniques (hierarchical planning, tool routing, memory, verification/critique, tree/graph search) and efficiency methods (distillation, quantization, caching, speculative decoding, retrieval) to improve latency, cost, and reliability for enterprise workloads. You will design and implement verifiable, auditable reasoning systems—spanning reasoning traces, intermediate state management, and outcome validation—to drive trustworthy outcomes in production. Partnering closely with applied scientists, research engineers, and product teams, you will take solutions from lab to production, delivering measurable impact in globally scaled intelligent applications. This role requires deep expertise in agentic and generative AI with a strong focus on planning and multi-step reasoning. Hands-on proficiency with modern ML/LLM stacks (e.g., Python, PyTorch/JAX, transformers, vector stores, orchestration frameworks) and systems performance techniques (KV-cache management, batching, routing, parallelization) is a must. Familiarity with post-training/fine-tuning (RLHF/RLAIF, DPO, PEFT), alignment and guardrails, and symbolic-neural hybrid methods is encouraged to partner effectively with modeling and platform teams.

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Responsibilities

The Principal Research Engineer will research, architect, and prototype next-generation agent planning and orchestration techniques. They will partner closely with applied scientists and product teams to take solutions from lab to production.