AI & ML Tech Lead/Architect

ccube; North Carolina; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Flexible Hybrid setup

High ownership

Collaboration with strong talent

Job summary

Ccube is seeking an AI & ML Tech Lead based in Raleigh, NC. The role requires a strong foundation in Python and microservices architecture. Ideal candidates will bridge traditional backend systems with modern AI platforms, working on real production AI systems.

Key responsibilities include designing scalable architectures and integrating AI/ML tools. Candidates should have over 5 years of backend development experience, especially with microservices and LLM frameworks.

The position offers a flexible hybrid setup and high impact in a collaborative environment.

Qualifications

• 5+ years of experience in backend development with Python.
• Proven experience designing and deploying microservices architectures.
• Familiarity with AI/ML concepts and LLM prompt engineering.

Responsibilities

• Architect and design scalable microservices in Python.
• Collaborate with AI/ML teams to integrate LLM tools.
• Lead technical discussions with stakeholders.

Skills

Backend development with Python

Microservices architecture

AI/ML concepts

LLM orchestration frameworks (LangChain, Agentic AI)

API design

Production-level RAG implementation

Containerization (Docker, Kubernetes)

Tools

CI/CD pipelines

AI platforms (OpenAI, Azure OpenAI, Anthropic, Hugging Face)

Job description

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., 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

• 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 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.

Nice-to-Have / Big Plus

• Experience with MCP, A2A, or similar AI infrastructure concepts.
• Knowledge of data pipelines & AI model lifecycle management.
• Prior experience architecting enterprise AI platforms.

Why Join Us?

• 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.