Solutions Architect

About the role

The Solutions Architect will own the technical side of Andromeda's largest customer engagements. They will partner with Sales to qualify opportunities, lead technical discovery, and scope evaluations against the customer's real success criteria. They will design cluster and workload architectures that map to business outcomes and own POCs end-to-end. After landing the deal, they will be the technical owner for the account, responsible for architecture reviews, capacity planning, performance and cost optimization, and technical workload reviews. They will also spot expansion needs and build the necessary assets for the SA team.

Responsibilities

• Win the technical evaluation
• Partner with Sales to qualify opportunities, lead technical discovery, and scope evaluations against the customer's real success criteria.
• Design cluster and workload architectures that map to business outcomes: time-to-first-token, tokens/sec, MFU, cost per training run, reliability targets.
• Own POCs end-to-end — scope, benchmarks, success metrics, timeline, stakeholder alignment.
• Land it and grow it
• 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.

Requirements

• 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.
• Strong Candidates May Have 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.

Qualifications

No specific qualifications are listed in the job posting.

Skills

No specific skills are listed in the job posting.

Benefits

No specific benefits are listed in the job posting.

Pay

No specific pay details are listed in the job posting.

Schedule

No specific schedule details are listed in the job posting.