AI Solutions Architect

Franklin Fitch; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Franklin Fitch is partnering with a technology client in New York to recruit a Senior AI Solutions Architect. This highly technical, customer-facing role focuses on the architecture of AI solutions, including deployment strategies and integration across cloud, DevOps and infrastructure.

You will work across AI, software engineering and cloud/DevOps to design scalable, secure AI systems for enterprise customers, translate requirements into architectures, and prototype and demo solutions.

Qualifications

• 5+ years in senior technical architecture or solutions architecture.
• Hands-on with LLMs, RAG pipelines, or AI agents.
• Strong cloud, containers, Kubernetes, and distributed systems knowledge.

Responsibilities

• Design scalable, secure AI solutions for enterprise customers.
• Translate business needs into practical technical architectures.
• Develop prototypes and deliver technical demonstrations.
• Collaborate across AI, software engineering and cloud/DevOps teams.

Skills

LLMs & AI agents

Cloud & Kubernetes

Distributed systems

Prototyping & demos

Customer engagement

Terraform & Ansible

Python

Tools

Kubernetes

Docker

Terraform

Ansible

CI/CD

Job description

I’m working with a technology client that is looking for a Senior AI Solutions Architect to join their team in a highly technical, customer-facing role.

This is not a traditional pre-sales Solutions Architect position. The focus is on the technical architecture of AI solutions — understanding how AI applications work, how they are deployed, and how the underlying cloud, DevOps and infrastructure layers fit together.

The Role

You’ll work across AI, software engineering and cloud/DevOps, helping design scalable, secure and reliable AI solutions for enterprise customers. You’ll translate customer requirements into technical architectures, develop prototypes and deliver technical demonstrations.

Key areas include:

• Generative AI, LLMs, RAG and Agentic AI
• AI platforms, infrastructure and inference
• Cloud-native and on-prem AI architectures
• Kubernetes, Docker and container orchestration
• Python, Terraform, Ansible and CI/CD
• Distributed systems, APIs and microservices
• Scalability, high availability, security and observability
• AI/ML platforms and MLOps

What We’re Looking For

We’re particularly interested in someone from a software engineering or DevOps background who has moved into AI, rather than a traditional infrastructure/networking architect.

You should have:

• 5+ years of Solutions Architecture or equivalent senior technical architecture experience
• Hands-on experience with LLMs, RAG pipelines and/or AI agents
• Experience across several AI disciplines such as AI platforms, AI infrastructure, Agentic AI, RAG or MLOps
• Strong understanding of cloud, containers, Kubernetes and distributed systems
• Experience building prototypes and demonstrating technical solutions
• Strong communication skills and the ability to engage directly with customers
• Experience translating business requirements into practical technical architectures

You don't need to be an expert across every technology in the specification. The team is looking for strong technical depth in several areas, combined with enough breadth to understand how the different AI, application and infrastructure layers work together.

Customer & Technical Exposure

You’ll have the opportunity to work directly with enterprise customers across industries including financial services and SaaS, supporting technical discovery, workshops, solution design and demonstrations.

The role is highly technical, but you'll also need to be comfortable explaining complex AI concepts to customers and presenting practical solutions rather than simply designing them behind the scenes.

Location & Compensation

Location: New York, NY

Working model: Hybrid

This is a strong opportunity for a technically hands‑on Software Engineer, DevOps Engineer, AI Engineer or Solutions Architect who has moved into AI and wants to work at the intersection of AI architecture, software engineering and enterprise customer solutions.