Solutions Architect

● Take customers from signature to first successful production training run: provisioning, environment setup, validation benchmarks, and the unglamorous debugging in between.

● Serve as the named technical owner for your accounts after launch. You’re responsible for architecture reviews, capacity planning, performance and cost optimization, and technical workload reviews.

● Spot expansion before the customer asks: where they're capacity-constrained, what's coming on their roadmap, and what it will take to serve it.

● Create the assets the SA team runs on: demo environments, benchmarking harnesses, reference architectures, onboarding runbooks, evaluation playbooks, and competitive material.

● Be the highest-signal feedback loop into Product, Engineering, and Research — recurring gaps, competitive losses, and what customers actually ask for once they're in production.

● 5+ years in customer-facing technical roles, including 2+ years in pre-sales (Solutions Engineer, Sales Engineer, Solutions Architect, or specialist SA).

● Direct experience selling or supporting GPU compute at a neocloud or GPU provider, or as an AI/HPC specialist at a hyperscaler or NVIDIA.

● Demonstrated ability to take a customer from evaluation into production and stay accountable for the outcome.

● Real fluency in large-scale training and inference: distributed training frameworks, multi-node topologies, InfiniBand/RoCE, storage and checkpointing, and where these break at scale.

● Comfort with Kubernetes and SLURM as scheduling environments customers actually run in.

● Enough Python to build a benchmark, a prototype, or an API integration yourself rather than waiting on engineering.

● A track record of owning technical evaluations in complex, multi-stakeholder deals and changing the outcome.

● Exceptional communication, able to hold a deep conversation with a distributed systems engineer and a CFO.

● Experience with frontier labs or AI-native companies as customers.

● Performance benchmarking, MFU analysis, or total-cost-of-training modeling.

● Having been the first or earliest SE somewhere.

● POCs convert reliably because evaluations are well-scoped, technically credible, and tied to customer ROI.

● Customers reach their first production training run fast, and what they saw in the POC is what they get.

● Accounts grow because you saw the constraint coming before the customer raised it.

● The assets you build let the next five SAs ramp in weeks instead of quarters.

● High-growth environment: Get in early at a company at the center of the AI infrastructure boom

● Competitive compensation: + meaningful equity

● Comprehensive benefits: for you and your dependents, including healthcare, dental, and vision coverage, 401(k), and unlimited PTO

Andromeda Cluster is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.