Senior Software Engineer - AI Agents & GenAI

We are seeking a highly motivated, hands-on Senior Software Engineer (AI Agents & GenAI) to join an enterprise technology team in Dubai. Operating within the Software Engineering Chapter, this role focuses on designing, building, and deploying autonomous AI agent solutions, custom tools/skills, and microservices integrated with enterprise platforms (including Oracle Fusion HCM Cloud).

The ideal candidate brings strong backend development experience in Node.js/TypeScript, deep expertise in LLM orchestration (LangChain/LangGraph), and practical skills in building reliable, multi-step agentic workflows and tool-calling mechanisms from ground up.

Requirements

Key Responsibilities1. AI Agent Development & Orchestration* Translate complex business requirements into working AI agent solutions using frameworks like LangChain, LangGraph, or Oracle AI Agent Studio.

• Design and execute multi-step agentic workflows (sequential, conditional, and parallel agent/tool calls, supervisor-worker patterns, and agent-to-agent handoffs).
• Implement advanced context management, model selection, caching, and guardrails to optimize for latency, cost, and hallucination reduction.
• Establish and manage workflow triggers across event-based, schedule-based (cron), webhook-based, and user-initiated execution flows.

2. Prompt Engineering & Custom Tooling* Write and refine advanced prompt architecture (system prompts, role-based prompting, few-shot/zero-shot design, chain-of-thought structuring, structured JSON/XML outputs).

• Build and maintain custom tools, skills, and functions for agents to perform data lookups, calculations, document generation, and external action executions.
• Protect AI solutions against prompt injection attacks and handle edge-case failures gracefully.

3. Backend Microservices & System Integration* Build and maintain scalable backend microservices using Node.js and TypeScript.

• Integrate AI agents with internal and external REST/SOAP APIs, managing authentication (OAuth, SSO, API Keys), response parsing, retry mechanisms, and error handling.
• Perform database operations across relational and non-relational database storage layers.
• Set up and manage version control (Git) and CI/CD pipelines for smooth agent and code deployment.

4. Testing, Monitoring & Maintenance* Thoroughly test agent behavior, evaluating non-deterministic outputs and edge cases systematically.

• Set up logging, tracing, and evaluation frameworks for production AI agent monitoring and debugging.
• Maintain clear architectural, API, and prompt documentation for long-term platform maintainability.

Technical Specifications & SkillsCore AI & LLM Stack (Essential)* LLM Fundamentals: Solid grasp of tokens, temperature, top_p, streaming data, context windows, and non-deterministic logic.

• Prompt Engineering & Tools: Expert in structured outputs, function/tool calling, guardrails, and advanced techniques (Chain-of-Thought, RAG / Vector Databases).
• Agentic Frameworks: Hands-on experience with LangChain, LangGraph, or similar agent frameworks; exposure to MCP (Model Context Protocol).
• API & Integration: Deep experience with REST/SOAP APIs, webhooks, and secure authentication (OAuth, SSO).

Backend & Engineering Stack (Essential)* Languages & Architecture: Strong proficiency in Node.js and TypeScript within a Microservices architecture.

• Databases & DevOps: Experience with Relational and NoSQL databases, Git version control, and CI/CD pipelines.

Preferred / Added Advantages* Experience with Oracle AI Agent Studio and Oracle Fusion HCM Cloud.

• Experience building multi-agent systems and supervisor/worker agentic patterns.
• Familiarity with AI monitoring, observability, and evaluation tools.

Qualifications & Experience* Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field.

• Experience: 3–5 years of hands-on experience building LLM-based applications, AI agents, and backend services in production environments.
• Soft Skills: Strong ownership mindset, analytical troubleshooting skills for AI systems, and excellent technical documentation capabilities.