Lead Developer / Application Architect (Agentic AI)
Job Title: Lead Developer / Application Architect
Location: Remote
Duration: 11 Months (Contract to Hire)
Role Overview
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.
Key Responsibilities
- 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
Required Skills & Experience
- 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