Avathon
Technical Architect - Forward Deployed Engineering
$170K–$220K
Pleasanton, California, United States +1 · Full-time · Posted Sep 23, 2026
- Location
- Pleasanton, California, United States
Austin, Texas, United States - Experience
- 8+ years, including at least 3 years in a lead architect or principal engineer role with direct delivery accountability.
- Education
- Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master’s preferred.
- Visa sponsorship
- Must be authorized to work in the United States without current or future company sponsorship.
About the job
Owns the architecture and production delivery of customer-specific industrial AI deployments, integrating Avathon’s platform with customers’ operational systems and workflows.
What you'll do
- Design and deliver AI architectures, knowledge graphs, agentic workflows, and Visual AI integrations for customer environments.
- Set technical standards, manage architectural risks, mentor engineers, and define AI evaluation and production observability practices.
- Lead customer technical discovery and engagement, including integration, security, cloud/edge infrastructure, and production handoff.
What they ask for
- 8+ years in software engineering, systems architecture, or technical delivery, including at least 3 years as a lead architect or principal engineer with direct delivery accountability.
- Track record owning architecture for large-scale production enterprise AI or industrial systems.
- Certification or demonstrated hands-on experience in data science, machine learning, or AI systems engineering.
- Bachelor’s degree in Computer Science, Engineering, or a related technical field; must be authorized to work in the United States without current or future company sponsorship.
Nice to have
- Master’s degree; active U.S. Government security clearance is a strong plus.
Pay
$170,000 - $220,000 USD base salary
Tools
Computational Knowledge Graph, Agent Foundry, VAIA, SCADA, OPC-UA/DA, MQTT, Python, AWS
AI focus
Designs generative and agentic AI workflows, knowledge-graph architectures, and Visual AI deployments; defines AI evaluation, monitoring, and continuous-improvement practices for production systems.
Model-written summary · the original posting is authoritative