AI Field Solutions Architect

Sierra Ventures; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness

Meals provided

Parental leave

Unlimited PTO

Visa sponsorship

Team building

Job summary

Reflection AI in San Francisco seeks Forward Deployed Engineers to own technical execution in customer engagements, from discovery to production delivery. You will work across the AI stack, including GPU orchestration, inference, and post-training, partnering with customer ML teams to deliver strategic engagements that shape reflections platform.

The role requires hands-on experience with multi-node GPU clusters, container orchestration, and deployment of large models, plus leadership in

Qualifications

• Strong technical fluency with Python, architecture, and system behavior.
• Track record leading complex technical projects across workstreams.
• Hands-on infra and inference experience: multi-node GPU clusters and production models.
• Agent engineering experience: shipping LLM-based agents and harnesses.
• 5+ years delivering technical systems; 2+ years in leadership roles.
• Customer-facing delivery mindset and ability to own end-to-end deployments.

Responsibilities

• Lead deep technical discovery and translate needs into feasible technical solutions.
• Own end-to-end proofs of concept, benchmarks, and evaluate latency, quality, and cost.
• Architect and build complex AI systems including agentic applications and model-serving infra.
• Identify patterns and model gaps; prototype and generalize to platform features.
• Define playbooks, reference architectures, and reusable assets for teams.
• Manage customer engagement plans and align stakeholders across workstreams.

Skills

Python development

Distributed systems

GPU orchestration

System architecture

Customer engagement

Leadership & ownership

Tools

Kubernetes

vLLM / SGLang

Job description

Reflection AI in San Francisco seeks Forward Deployed Engineers to own technical execution in customer engagements, from discovery to production delivery. You will work across the AI stack, including GPU orchestration, inference, and post-training, partnering with customer ML teams to deliver strategic engagements that shape reflections platform.

The role requires hands-on experience with multi-node GPU clusters, container orchestration, and deployment of large models, plus leadership in