Senior Enterprise AI Solutions Architect (Hands-On)

Alvarez & Marsal; New York (NY); On-site; USD 195,000 - 230,000; Full time

Benefits offered by this job

Healthcare plans

401(k) retirement savings

Paid time off & holidays

Job summary

Alvarez & Marsal is seeking an Enterprise AI Solutions Architect to lead the design and delivery of scalable, secure AI-enabled solutions across frontend and backend systems. The role combines architecture leadership with hands-on development, prototyping, and troubleshooting to accelerate production delivery.

You will collaborate with product managers, stakeholders, and offshore teams to translate requirements into scalable technical architectures and production-ready implementations, while

Qualifications

• 10+ years of software engineering, solution architecture, or full-stack development experience.
• Demonstrated ability to operate as a hands-on architect with ~50% hands-on work.
• Deep experience designing and deploying enterprise solutions within Microsoft Azure.
• Generative AI and/or Agentic AI technologies and architectures.

Responsibilities

• Own the end-to-end architecture of enterprise AI and technology solutions across frontend apps, backend services, APIs, data platforms, AI services, and Azure cloud infrastructure.
• Translate business and product requirements into scalable, secure solution architectures and define the technical roadmap to production.
• Develop architecture diagrams, solution designs, integration patterns, data flows, technical specs, and implementation approaches.

Skills

Azure

Generative AI

LLMs

RAG

APIs

Distributed systems

Security

Leadership

CI/CD

Tools

Azure

Job description

Alvarez & Marsal is seeking an Enterprise AI Solutions Architect to lead the design and delivery of scalable, secure AI-enabled solutions across frontend and backend systems. The role combines architecture leadership with hands-on development, prototyping, and troubleshooting to accelerate production delivery.

You will collaborate with product managers, stakeholders, and offshore teams to translate requirements into scalable technical architectures and production-ready implementations, while