The role

We are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.

In AI infrastructure, PoC success does not always guarantee production success. This role exists to ensure that what we commit to with customers is scalable, efficient, and aligned with platform strategy.

We are looking for a Senior Sales Engineer to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions.

You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:

Revenue quality
Engineering focus
Product evolution
Customer trust at scale

You’re welcome to work remotely from the United States.

Your responsibilities will include:

Strategic Technical Discovery

Lead deep technical discovery with engineering teams and technical founders
Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies
Translate customer ambition into production-feasible architecture.
Identify hidden technical risks early

Commercial Acceleration

Partner tightly with Sales on strategic deals
Influence deal strategy through architectural clarity
Prevent misaligned commitments before engineering allocation
Increase PoC-to-production conversion by ensuring technical realism

PoC Architecture & Validation

Define measurable success criteria (latency, TTFT, throughput, cost envelope)
Classify workload complexity and required optimization depth
Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)
Drive structured Go / No-Go decisions
Prevent uncontrolled customization or hidden R&D

Pattern Recognition & Platform Leverage

Identify recurring configuration patterns across customers
Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)
Surface structured insights to Product and Engineering
Help evolve platform capabilities based on real workload data

We expect you to have:

Deep understanding of AI inference systems and GPU-backed infrastructure
Experience with LLM workloads and performance-sensitive environments
Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).
Ability to reason about latency, throughput, cost, and architecture tradeoffs
Strong customer presence with engineering-first organizations
Comfort challenging assumptions and pushing back constructively
Commercial awareness – you understand that engineering time is a strategic resource

Preferred Technical Stack

Programming Languages– Python
Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs
Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent
API and Web Frameworks– FastAPI, Flask
MLOps and DevOps tools– Kubernetes (K8s), Docker, Git
Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

What Success Looks Like

Strategic deals are technically sound before engineering engagement
PoCs are clearly scoped and economically justified
Engineering capacity is allocated predictably
Conversion to production improves
Customers view you as a trusted architectural advisor

Key employee benefits in the US:

Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
401(k) plan: Up to 4% company match with immediate vesting.
Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
Remote work reimbursement: Up to $85/month for mobile and internet.
Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.

Compensation

We offer competitive salaries, ranging from $152k - 228k base + RSU's and performance bonus's.