Forward Deployed AI Engineer

Forward Deployed AI Engineer (Post-Sales) 📍 Location: San Mateo, CA 🏢 Work Model: In-office, 4 days per week ✈️ Travel: Required for customer deployments as needed We’re looking for a highly technical, customer-focused Forward Deployed AI Engineer to lead customer deployments, production adoption, and technical integrations across complex cloud, on-premises, and hybrid environments.

You’ll act as a trusted technical partner to strategic customers, working closely with Sales, Research, and Engineering to translate customer requirements into scalable solutions, troubleshoot complex infrastructure challenges, and drive long-term platform adoption.

This role is ideal for someone who combines strong infrastructure engineering skills with customer-facing experience and enjoys solving ambiguous, technically challenging problems.

Key Responsibilities

• Lead customer onboarding, deployment, production rollout, and ongoing adoption of AI infrastructure platforms.
• Own technical engagements end to end, including solution architecture, implementation, deployment planning, and customer success.
• Design and optimize scalable, secure systems across compute, storage, networking, and distributed infrastructure.
• Deploy and adapt solutions across AWS, GCP, Azure, and on-premises Kubernetes environments.
• Troubleshoot complex infrastructure issues involving networking, storage, compute orchestration, and performance optimization.
• Partner with Sales, Engineering, and Research teams to support technical evaluations, translate customer needs into solutions, and influence product roadmap priorities.
• Monitor deployment progress, workload health, resource utilization, and adoption metrics; communicate updates to technical and executive stakeholders.

Required Qualifications

• 5+ years of experience in solution architecture, customer engineering, infrastructure engineering, technical consulting, or technical program delivery.
• Strong hands-on experience with distributed systems, data infrastructure, and cloud or hybrid compute environments.
• Experience deploying AI/ML workflows or complex backend systems involving Kubernetes, data pipelines, networking, and large-scale infrastructure.
• Strong proficiency in Python, SQL, or similar programming languages, with the ability to debug technical issues end to end.
• Hands-on experience across multiple cloud platforms, including AWS, GCP, and Azure, covering compute, storage, networking, and IAM.
• Proven ability to adapt and deploy distributed systems across different infrastructure environments.
• Experience with infrastructure as code (IaC), configuration management, and multi-environment deployments.
• Strong communication and stakeholder management skills, with experience leading complex technical projects.
• Willingness to travel to customer sites for critical deployments and technical engagements.
• Ideal Candidate Profile A hands-on engineer who can move between infrastructure architecture, debugging, customer conversations, and production deployment.
• You should be comfortable navigating ambiguity, solving distributed systems challenges, and turning complex customer requirements into reliable, scalable AI infrastructure solutions.
• Interested?
• Reach out to discuss the opportunity.