Solution Architect Engineer

PrimaLabs is building AI infrastructure and tools that help enterprises deploy and scale intelligent systems faster. Our focus is on making AI production-ready from experimentation to reliable deployment.

As one of our first customer-facing technical hires, you will work directly with early enterprise customers and the founding team to ensure successful deployments and long-term adoption.

Role Overview

Were looking for anengineer who will own the technical relationship with our early customers.

You will lead onboarding, deployment, and ongoing technical success for enterprise accounts, while also helping shape the product by translating real customer requirements into actionable feedback for the engineering team.

This role sits at the intersection of engineering, product, and customer success.

Key Responsibilities

Customer Deployment & Onboarding

• Lead technical onboarding for new enterprise customers
• Deploy PrimaLabs solutions within customer environments (cloud / on-prem)
• Ensure smooth integration with customer ML, data, and infrastructure stacks
• Diagnose and resolve deployment issues

Customer Success

• Act as the primary technical point of contact for early customers
• Drive adoption and ensure customers achieve measurable value
• Build trusted relationships with technical stakeholders
  

Deployment Playbooks

• Build repeatable deployment frameworks and documentation
• Standardize onboarding processes and architecture patterns
• Improve time-to-value for future customers

Product Feedback Loop

• Translate real customer needs into clear product feedback
• Work closely with product and engineering teams to prioritize improvements
• Influence roadmap based on enterprise requirements

Technical Evangelism

• Lead architecture discussions with VPs of Engineering, Heads of Data, and ML leaders
• Deliver technical demos and workshops
• Represent customer needs internally

Required Background

• 4+ years in MLOps, DevOps, and AI infrastructure
• Experience deploying ML/AI systems in production environments

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  Strong understanding of:
• Cloud platforms (AWS, GCP, Azure)
• Containers (Docker, Kubernetes)
• ML infrastructure / pipelines
• Comfortable working directly with enterprise engineering leadership
• Excellent communication and problem-solving skills

Experience with:

• LLM infrastructure
• Model deployment frameworks
• Vector databases / retrieval systems
• Prior experience in early-stage startups
• Background in solutions engineering or developer relations

What Makes This Role Unique

• Founding technical hire in customer success
• Direct influence on product direction
• Opportunity to define deployment playbooks used by all future customers
• Work closely with the founding team and early enterprise clients