AI/ML Lead-Architect

Position:- AI/MLTech Lead-ArchitectLocation: Raleigh, NC (Hybrid)Job Type: W2/FT Experience Level: 8-15 Years Required Skills- Claude, Vibe Coding, Data Scientist, MCP, Agentic AI, LLM understanding, RAG. Architecture end to end, built systems. We are seeking a highly skilled AI/ML Leader with a strong foundation in Python and microservices architecture, capable of bridging the gap between traditional backend systems and modern AI/ML platforms. The ideal candidate will have experience or a strong interest in LLM-based frameworks (e.g., LangChain, Agentic AI), and be capable of designing scalable, intelligent solutions that integrate with major AI platforms.

Key Responsibilities:

· Architect and design scalable, secure, and high-performance microservices using Python.

· Collaborate with AI/ML teams to integrate LLM-based tools and frameworks into enterprise applications.

· Understand and work with MCP (Model Context Protocol), A2A (Agent-to-Agent) communication, and LLM orchestration frameworks like LangChain and Agentic AI.

· Evaluate and recommend AI platforms and tools for enterprise use cases.

· Translate business requirements into technical solutions that leverage both traditional and AI-driven components.

· Lead technical discussions with stakeholders, including product managers, data scientists, and platform teams.

· Ensure architectural alignment with enterprise standards and best practices.

Required Skills & Experience:

· 8+ years of experience in backend development with Python.

· Proven experience designing and deploying microservices architectures.

· Familiarity with AI/ML concepts, especially LLMs, prompt engineering, and AI agents.

· Understanding of LangChain, Agentic AI, or similar LLM orchestration frameworks.

· Experience integrating with AI platforms (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face).

· Strong understanding of API design, event-driven systems, and cloud-native architectures.

· Excellent communication and stakeholder management skills.

Production-level RAG implementation experience.· Hands-on experience with LLM-based applications or AI agent frameworks.

· Exposure to MCP, A2A, or similar AI infrastructure concepts.

· Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.

· Knowledge of data pipelines and AI model lifecycle management

Why Join Us?Work on real production AI systems, not just POCsDesign next-gen Agentic & LLM-powered architecturesHigh ownership, high impact roleFlexible Hybrid setupCollaborate with strong engineering & AI talent