Forward Deployed AI Engineer

Forward Deployed AI Engineer – Generative AI

Location: New York, NY

Compensation: $180,000–$230,000+ base

3-5 days per week in Manhattan office

About the Company

Brio Digital is working with a leading AI technology company that partners with frontier AI research organisations and major global enterprises to accelerate the development and deployment of advanced AI systems.

The company operates at the cutting edge of Generative AI, combining specialist engineering talent, advanced AI infrastructure and research capabilities to help organisations build and deploy sophisticated AI systems.

For enterprise customers, the organisation develops proprietary AI solutions that integrate directly into mission-critical workflows, helping businesses move from AI experimentation into scalable, production-grade applications.

Its teams include experienced AI and technology professionals from some of the world’s leading technology companies, research institutions and high-growth startups.

The Role

We’re looking for a Forward Deployed AI Engineer to work directly with enterprise customers to design, build and deploy production-grade Generative AI applications.

This is a highly hands-on engineering position sitting at the intersection of software engineering, Generative AI and customer delivery .

You’ll embed within customer projects and take ownership of solutions from initial discovery and architecture through to development and production deployment.

You’ll work extensively with Python, LangChain, LangGraph and Large Language Models , solving complex real-world problems while acting as a trusted technical partner to customers.

This role would suit an engineer who enjoys building rather than advising from the sidelines – someone comfortable moving between customer conversations, architecture decisions and writing production code.

Responsibilities

• Lead the end-to-end delivery of Generative AI applications , from initial customer discovery through to production deployment.
• Work directly with customers to understand complex business and technical challenges and translate them into effective AI solutions.
• Architect and build scalable applications using Python, LangChain, LangGraph and LLM frameworks .
• Design production-grade systems using modern engineering patterns including APIs, microservices and event-driven architectures .
• Act as a trusted technical advisor to customers throughout the delivery lifecycle.
• Write clean, maintainable production code and develop reusable components that accelerate future deployments.
• Deploy and operate AI applications across AWS, Azure and/or GCP .
• Ensure applications are secure, scalable and performant in production environments.
• Collaborate with product, Machine Learning and engineering teams to influence product roadmaps and platform capabilities.
• Improve deployment tooling, engineering pipelines and delivery methodologies to reduce time-to-value.
• Take ownership of multiple technical workstreams and customer deployments simultaneously.

Required Experience

• 5–8+ years of experience across software engineering, solutions engineering or a similar technical discipline.
• Strong hands-on Python engineering experience.
• Commercial experience with LangChain and/or LangGraph .
• Strong SQL skills.
• Demonstrable experience designing and deploying Generative AI applications into production .
• Strong software architecture experience, including APIs, microservices and event-driven systems .
• Experience building and deploying applications using AWS, Azure and/or GCP .
• Experience working directly with customers or senior technical stakeholders.
• Excellent communication skills with the ability to translate complex technical concepts into clear customer-facing conversations.
• Comfortable operating autonomously and owning technical delivery from discovery through production.
• Ability to manage multiple deployments and technical workstreams in parallel.

Desirable Experience

Experience in any of the following would be particularly valuable:

• Retrieval-Augmented Generation (RAG)
• LLM fine-tuning
• Agentic AI / multi-agent systems
• AI/ML operations and productionisation
• CI/CD pipelines
• Infrastructure-as-Code using Terraform or Pulumi
• Docker and Kubernetes
• Startup or high-growth technology environments
• Technology consulting or…