Senior Manager of Account Solutions Architecture; Engaged

Responsibilities

• As Manager / Senior Manager, Solutions Architecture, you’ll lead the Solutions Architects who own our most complex customer deployments across AWS, GCP, Azure, and on-prem environments in [REGION]
• This is a player-coach role: you’ll keep your hands on the work — architecture reviews, critical escalations, the occasional deployment you run yourself — while building the team and the systems that scale past you
• You’ll own hiring and ramp in region, coverage across accounts and time zones, and the standard for how deployments get executed and documented. You’ll be the technical escalation point for customer infrastructure failures and the person regional Sales and Field Engineering leadership come to when a deal turns on a technical outcome
• And you’ll convert recurring customer pain into roadmap input and reusable assets — reference architectures, runbooks, automation, and enablement your team delivers in the field
• Lead and grow a team of Solutions Architects covering [REGION], including hiring, onboarding, ramp plans, and performance management
• Stay hands-on in customer environments — architecture reviews, deployment escalations, and root-cause analysis on Kubernetes, networking, storage, and cloud infrastructure issues
• Own the regional coverage model: account assignment, on-call, escalation paths, and response expectations across time zones
• Partner with Sales Engineering, Field Engineering, and Support leadership on pre-sales technical validation, deployment planning, and post-sales adoption
• Drive leverage: turn repeat issues into reference architectures, Terraform and Helm assets, runbooks, and enablement content instead of repeat escalations
• Deliver and coach the team on technical workshops, demos, and customer enablement sessions
• Feed structured field evidence into Product and Engineering to influence roadmap and deployment tooling priorities

• Strong Linux/Unix command line experience
• Hands-on expertise with Docker, Kubernetes, and Helm charts, plus networking fundamentals (DNS, TLS, ingress, load balancing, proxies) and cloud-managed services (e.g., MySQL, object stores)
• 3+ years managing a customer-facing technical team (Solutions Architecture, SRE, TAM, professional services, or field engineering) with direct hiring and performance-management responsibility — 5+ years for Senior Manager
• Working proficiency in Python and familiarity with ML workflows or tooling
• Experience supporting both multi-tenant SaaS and customer-managed / on-prem deployments of the same product
• 7+ years total hands-on infrastructure, platform, or SRE experience — 10+ for Senior Manager
• Demonstrated track record of systematically diagnosing and resolving production infrastructure issues in customer-owned environments
• Proficiency with at least one cloud platform (AWS, GCP, Azure); working knowledge of more than one is a plus
• Demonstrated experience delivering technical workshops, demos, or enablement sessions to customer engineering teams
• Production experience with Infrastructure as Code, preferably Terraform
• You love diving into infrastructure problems and solving them systematically — and you get more satisfaction from your team solving them than from solving them alone
• You’re an expert in building and running containerized, distributed systems
• We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk
  
  You’d rather write the runbook once than answer the same escalation five times
• You’re comfortable being the calm one on a customer bridge call at 2am, and the one who makes sure it doesn’t happen again
• You’re curious about how to scale complex ML systems in production environments
• Experience with GPU infrastructure and distributed training workloads
• SaaS, web service, or distributed systems operations experience at scale
• Deep proficiency in Kubernetes design patterns, including Operators and CRDs
• Familiarity with data engineering and MLOps tooling (e.g., Ray, Kubeflow, Slurm, Airflow, Sage Maker, Vertex AI)
• Experience with air-gapped, sovereign, or regulated-industry deployments
• Experience building a regional technical team from a small headcount into a durable function with defined coverage, on-call, and ramp