AI Architect

Hello,

Greetings from Clifyx.

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Job title: AI Architect
Work Location: New York, NY (Hybrid-Onsite)

Job Details:
We are seeking a highly skilled FDE/Architect with deep expertise in Generative AI, LLMs, and agent-based architecture. The ideal candidate should be an exceptional Python engineer with hands-on experience building scalable, production-grade systems, GenAI solutions, MCP-based tooling, and AI/ML deployments at scale. This role requires an engineering mindset, strong problem-solving abilities, and the ability to work closely with business stakeholders to translate requirements into robust technical architectures.

Key Responsibilities:

1. GenAI & LLM Expertise
Strong understanding of state-of-the-art GenAI models, especially OpenAI s latest LLMs (GPT-4o, GPT-5 series, o-series, custom models, etc.).
Should have strong knowledge of GenAI guardrails, safety mechanisms, and evaluation techniques to ensure reliable, compliant, and high-quality GenAI solutions
Hands-on experience with OpenAI SDK, LangChain, LangGraph, and other agentic frameworks.

2. Agentic Systems & MCP Architecture
Proven experience designing and developing AI Agents, tools, workflows, and agentic architectures.
Strong expertise in building and managing MCP (Model Context Protocol) servers and clients.
Ability to build custom MCP tools, integrate them into larger agent architectures, and expose them to various agentic clients.
Knowledge of Arcade MCP registry is highly advantageous.

3. Python Engineering & System Design
Expert-level experience in Python, writing clean, modularized, scalable, production-grade code.
Hands-on experience with multithreading, multiprocessing, API development (FastAPI/Flask), and distributed system patterns.
Strong fundamentals in Unix / Linux, scripting, and orchestration.

4. Data Engineering & Databases
Proficiency working with Vector Databases such as Redis Vector Store, ElasticSearch, Pinecone (optional).
Good understanding of Graph Databases (Neo4j experience is a plus).
Strong working knowledge of SQL databases (MySQL) and cloud data platforms like Snowflake.
Familiarity with Snowflake Cortex and Snowflake s latest GenAI capabilities.

5. Deployment & MLOps
Experience deploying AI/ML and GenAI solutions at scale on Kubernetes (K8s).
Understanding of CI/CD pipelines, containerization (Docker), and scalable cloud architectures.

6. Consulting & Engineering Mindset
Ability to collaborate closely with clients, understand business requirements, and translate them into technical solutions.
Capability to quickly build POCs, create architecture diagrams, and define a clear roadmap to production rollout.
Strong analytical, communication, and stakeholder management skills.
Proactive, self-driven, and capable of working in a fast-paced environment.