Senior AI Platform Deployment Engineer

About the Opportunity

An innovative venture-backed technology company is transforming how large organizations deploy and manage advanced artificial intelligence solutions in production environments. The organization develops enterprise-grade platforms that enable businesses to operationalize AI safely efficiently and at scale while maintaining governance transparency security and performance standards.

As adoption of AI accelerates across regulated industries organizations require robust frameworks to ensure reliability compliance observability and operational control. This team is building the infrastructure layer that enables enterprises to confidently deploy and govern AI-powered systems in mission-critical environments.

We are seeking a highly technical customer-oriented engineer who thrives at the intersection of software engineering platform deployment enterprise architecture and AI implementation.

This is a high-impact role working directly with enterprise customers and internal product teams to ensure successful deployment and adoption of advanced AI solutions.

• Lead deployment and implementation initiatives for enterprise AI platforms across complex customer environments.
• Collaborate directly with customer engineering infrastructure architecture and operations teams to operationalize AI-powered solutions.
• Design build and support integrations across APIs cloud platforms enterprise applications security frameworks and governance systems.
• Troubleshoot sophisticated deployment performance scalability and reliability challenges.
• Translate customer requirements and implementation feedback into product enhancements and engineering priorities.
• Guide organizations through technical operational security and compliance considerations associated with AI adoption.
• Partner with stakeholders across engineering security risk management compliance infrastructure and executive leadership teams.
• Develop deployment best practices implementation methodologies and operational playbooks.
• Support production environments by identifying root causes optimizing system performance and ensuring successful adoption.
• Act as a trusted technical advisor during the full customer lifecycle.

• Bachelors degree in Computer Science Engineering Information Systems or a related technical discipline.
• Approximately 6 10 years of professional experience in software engineering platform engineering infrastructure engineering solutions engineering or technical implementation roles.
• Strong experience working with:
  • Kubernetes
  • Distributed systems
  • Cloud-native architectures
  • APIs and integrations
  • Infrastructure automation
  • Platform engineering
• Hands-on experience supporting customer deployments in production environments.
• Ability to read understand troubleshoot and write production-quality code and automation scripts.
• Experience working directly with technical customer stakeholders.
• Strong understanding of enterprise software deployment lifecycles.
• Ability to independently solve complex technical challenges with limited direction.
• Comfortable operating in fast-paced high-growth environments.

Candidates will stand out if they have experience with:

• Generative AI platforms and large language model ecosystems.
• AI observability evaluation monitoring or governance frameworks.
• Retrieval-Augmented Generation (RAG) architectures.
• Agentic AI workflows and orchestration platforms.
• Enterprise AI deployment programs.
• Cloud infrastructure platforms (AWS Azure or GCP).
• MLOps AI operations or platform reliability engineering.
• Consulting implementation or solutions engineering experience within high-growth technology organizations.
• Working with regulated industries such as financial services healthcare insurance public sector or government.