Lead Developer / Application Architect (Agentic AI)

• Design, develop, and deploy Agentic AI systems capable of autonomous reasoning, task execution, and multi-step workflows
• Architect scalable and modular AI-driven applications aligned with business requirements
• Build and integrate LLM-powered agents, orchestration frameworks, and tool-use pipelines
• Develop end-to-end application logic integrating AI agents with APIs, databases, and enterprise systems
• Lead development of multi-agent systems including coordination, memory management, and planning mechanisms
• Optimize application performance, reliability, and scalability in production environments
• Collaborate with cross-functional teams including product, engineering, and DevOps
• Ensure code quality, best practices, and maintainability across the development lifecycle
• Mentor junior developers and provide technical leadership where required

We are seeking a highly skilled Lead Developer / Application Architect with deep expertise in Agentic AI systems. This role is focused on hands-on development and architecture of intelligent, autonomous applications capable of decision-making, planning, and execution.

The ideal candidate will be a strong engineering-focused professional, not a data scientist, with experience designing and building scalable AI-driven applications using modern frameworks and tools., * Strong experience as a Developer or Application Architect (not data-science focused)

• Hands-on expertise in Agentic AI / Autonomous AI systems development
• Proven experience working with:

• LLM frameworks (e.g., LangChain, Semantic Kernel, AutoGen, etc.)
• Prompt engineering and agent orchestration

• Solid programming skills in Python, JavaScript/TypeScript, or similar languages
• Experience in building API-driven and microservices-based applications
• Strong understanding of:

• AI agent architectures (ReAct, Plan-and-Execute, multi-agent systems)
• Memory handling, vector databases, and context management

• Experience integrating AI systems with:

• External tools and APIs
• Enterprise systems and workflows

• Familiarity with cloud platforms (Azure, AWS, or Google Cloud Platform)
• Strong problem-solving and system design skills

Preferred Qualifications

• Experience deploying AI applications in production environments
• Knowledge of RAG (Retrieval-Augmented Generation) architectures
• Familiarity with containerization tools (Docker, Kubernetes)
• Exposure to CI/CD pipelines and DevOps practices
• Experience building enterprise-grade AI applications