Application Development & Support Analyst

India·Punemid

Other

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Quick Summary

Key Responsibilities

Design, configure, and deploy AI agents capable of reasoning, planning,

Technical Tools

Other

Short Description for Internal Candidates

Job Summary The Oracle SCM AI Agent Developer will be responsible for designing, implementing, and supporting AI-driven solutions to automate processes, improve operational efficiency, and enhance business decision-making. The role focuses on agentic AI systems, combining large language models (LLMs), enterprise data, APIs, and orchestration logic to deliver secure, scalable, and context-aware solutions.

Description for Internal Candidates

Responsibilities

~2 min read

→Design, configure, and deploy AI agents capable of reasoning, planning, and executing multi-step tasks
→Build prompt orchestration and agent workflows using LLMs
→Implement and support Oracle Cloud solutions with AI-driven automation
→Integrate AI agents with third-party applications
→Customize AI agent behavior using Oracle-native tools, workflows, and APIs
→Translate business requirements into scalable, AI-enabled solutions
→Optimize, monitor, and troubleshoot AI agent performance
→Ensure data security, governance, and compliance in AI implementations
→Collaborate with cross-functional teams and business stakeholders
→Provide technical documentation, knowledge transfer, and ongoing support
→Implement Retrieval-Augmented Generation (RAG) using structured and unstructured enterprise data
→Bachelor’s degree in Information Technology, Process Management, or a related field, or equivalent experience
→Minimum 8+ years of hands-on experience in Oracle Fusion customizations using REST APIs
→Hands-on exposure to Oracle AI Agent Studio
→Ability to design Supervisor agents, Sequential agents, and Workflow agents
→Practical understanding of enterprise Generative AI and Large Language Models (LLMs)
→Experience in prompt engineering for structured enterprise use cases, grounding LLM responses with enterprise data, and implementing RAG patterns
→Understanding of hallucination risks and mitigation techniques
→Strong understanding of enterprise AI security and governance requirements
→Experience implementing role-based permissions, approval checkpoints, and human-in-the-loop controls for AI agents
→Knowledge of data privacy, access control, and regulatory considerations in AI-enabled systems
→Experience integrating applications with external systems using REST APIs, SOAP web services, etc.

Requirements

~1 min read

Behavioral & Professional Competencies:

Business Knowledge: Demonstrates strong knowledge of current and emerging policies, practices, trends, technologies, and information related to the business and organization
Communication: Demonstrates excellent written and verbal communication and listening skills
Initiative: Works independently and is highly motivated to take ownership and embrace new challenges
Judgment / Decision Making: Makes sound decisions based on analysis, experience, and good judgment
Managing & Adapting to Change: Readily adapts to shifting priorities and strategic direction within a geographically distributed organization
Professionalism: Exhibits professionalism in all aspects of performance and conduct
Teamwork: Effectively collaborates across functions to achieve shared goals
Results-Oriented: Demonstrates strong accountability and consistently meets or exceeds objectives