Principal AI/ML Architect for Enterprise GenAI & Cloud

Slalom; Miami (FL); Hybrid; USD 157,000 - 196,000; Full time

Job summary

Slalom is seeking an AI/ML Architect to design and deliver production-grade AI systems combining machine learning, generative AI, and agentic workflows across AWS, Azure, and Google Cloud. You will lead cross-functional teams and shape enterprise AI strategies.

Responsibilities include securing architectures, governance, and practical deployment patterns while mentoring delivery teams. This role emphasizes responsible AI and client-focused outcomes in a hybrid work environment.

Qualifications

• 6+ years of experience implementing ML/AI solutions in production.
• 3+ years of experience in professional consulting or IT services.
• Hands-on experience designing production AI systems with end-to-end architecture.
• Deep understanding of GenAI patterns including RAG, embeddings, vector/search.
• Experience with agentic AI architecture patterns and workflows.

Responsibilities

• Architect and deliver enterprise-scale AI systems across data products and pipelines.
• Design secure, scalable cloud-native and hybrid architectures (AWS, Azure, Google Cloud).
• Lead AI solution design across generative and agentic AI use cases.
• Enable production GenAI adoption with tool calling, orchestration, and memory patterns.
• Define AI evaluation, observability, and reliability patterns with automated evals and monitoring.
• Champion Responsible AI and AI security practices across governance and privacy.

Skills

ML/AI production

Generative AI

Python

Cloud platforms

LangChain

MLOps

Kubernetes

AI security

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Haystack

CrewAI

Hugging Face

Job description

Slalom is seeking an AI/ML Architect to design and deliver production-grade AI systems combining machine learning, generative AI, and agentic workflows across AWS, Azure, and Google Cloud. You will lead cross-functional teams and shape enterprise AI strategies.

Responsibilities include securing architectures, governance, and practical deployment patterns while mentoring delivery teams. This role emphasizes responsible AI and client-focused outcomes in a hybrid work environment.