AI & ML Tech Lead/Architect
Job in
Raleigh, Wake County, North Carolina, 27601, USA
Listed on 2026-06-27
Listing for:
Ccube
Full Time
position Listed on 2026-06-27
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
AI & ML Tech Lead
Location: Raleigh, NC (Hybrid)
Job Type: Full Time / W2 Only
Experience Level: 8-15 Years
Required Skills: Claude, Vibe Coding, Data Scientist, MCP (Model Context Protocol), 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, who can bridge 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., Lang Chain, 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 Lang Chain 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.
- 5+ 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 Lang Chain, 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.
- Experience with MCP, A2A, or similar AI infrastructure concepts.
- Knowledge of data pipelines & AI model lifecycle management.
- Prior experience architecting enterprise AI platforms.
- Work on real production AI systems, not just POCs.
- Design next-generation Agentic & LLM-powered architectures.
- High ownership, high impact role.
- Flexible Hybrid setup.
- Collaborate with strong engineering & AI talent.
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