SOLUTIONS ENGINEER - PRE-SALES
LOCATION: REMOTE/SF-HYBRID · FULL-TIME
About Andromeda
Andromeda Cluster was founded by Nat Friedman and Daniel Gross to give early-stage startups access to the kind of scaled AI infrastructure once reserved only for hyperscalers.
We began with a single managed cluster — but it filled almost instantly. Since then, we’ve been quietly building the systems, network, and orchestration layer that makes the world’s AI infrastructure more accessible.
Today, Andromeda works with leading AI labs, data centers, and cloud providers to deliver compute when and where it’s needed most. Our platform routes training and inference jobs across global supply, unlocking flexibility and efficiency in one of the fastest-growing markets on earth.
Our long-term vision is to build the liquidity layer for global AI compute. We are expanding to new frontiers to find the brightest that work in AI infrastructure, research and engineering.
The Role
We're hiring our first Solutions Engineer to own the technical side of our largest deals. You will be the technical face of Andromeda to frontier labs and enterprises evaluating Andromeda to train and serve their models.
You'll be the person in the room who can go from a CTO's roadmap to an interconnect topology without losing either audience. You are responsible for technical discovery, architecture design, benchmarking, POC delivery, and the technical case for why a customer should move a nine-figure training run onto our platform.
This is a pre-sales role, and it's greenfield. There is no SE playbook here yet; no demo environment, no evaluation template, no reference architectures. You'll build them, and they'll become how Andromeda sells for years. If you've been the SE who quietly built all of that at your last company and want to do it on purpose this time, this is that role.
What You’ll Do
● You’ll sit in the room from the first technical call through the signed contract on our largest deals.
● 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, and hand off cleanly to delivery.
● Run credible technical conversations with research leads, platform teams, and infrastructure and security owners, and translate between them and their executives.
● Build the SE function from zero: demo environments, benchmarking harnesses, reference architectures, evaluation playbooks, competitive and objection-handling material.
● Shape the deal strategy directly with sales leadership: you’ll weigh in on how we position against competitors, where to hold firm technical and where to flex, and why we win or lose. That signal also feeds Product, Engineering and Research on what’s actually blocking deals at scale.
What We’re Looking For
● 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.
● 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.
What Success Looks Like
● POCs convert reliably because evaluations are well-scoped, technically credible, and tied to customer ROI.
● Sales cycles compress because technical objections get resolved in the first conversation, not the fifth.
● The assets you build let the next five SEs ramp in weeks instead of quarters.
Why You’ll Love It Here
● High-growth environment: Get in early at a company at the center of the AI infrastructure boom
● Ownership: First HPC Architect for the solutions engineering team, you’ll get to build this function from the ground up
● Competitive compensation: + meaningful equity
● Comprehensive benefits: for you and your dependents, including healthcare, dental, and vision coverage, 401(k), and unlimited PTO