The job, in the employer's words
About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Serve as the lead technical advisor for a set of key accounts, shepherding each one from initial setup through live production use of a software platform. The work involves designing secure, scalable architectures in varied customer environments and collaborating with internal teams to convert customer needs into technical plans. Occasional visits to customer locations are expected.
What you'll do
- Lead each key account through setup, installation and go-live from beginning to end.
- Act as the main technical contact, building lasting relationships and encouraging adoption in complex hybrid and self-hosted environments.
- Design secure, scalable workflows that span compute, storage, networking and distributed systems across multiple cloud providers and on-prem Kubernetes.
- Collaborate with sales, engineering and research colleagues to shape technical approaches that fit customer needs.
- Bring customer feedback back to the product team to inform the roadmap.
- Visit customer sites as required for important engagements.
Requirements
What we're looking for
- 5+ years in a customer-facing technical role, such as solutions or implementation engineering.
- Solid background in distributed systems, data platforms and self-hosted or hybrid infrastructure.
- Deep working knowledge of the major cloud providers, including compute, storage, networking and identity management.
- A track record of installing software inside large organizations' own infrastructure.
- Practical experience training machine learning models and a firm understanding of the stages of model training.
- Proficiency in Python and AWS, with the ability to troubleshoot and take part in technical discussions throughout a project.
- Skill at turning vague customer needs into clear architecture.
- Ownership of the complete customer lifecycle after a sale, including onboarding, optimization and creating processes and playbooks from zero.
- Comfort working in a startup or other fast-changing, ambiguous setting.
- A technical degree, ideally in computer science or equivalent.
- Willingness to travel roughly 15% of the time.
Bonus points
- Familiarity with additional cloud platforms, self-hosted infrastructure or ML tooling.
Benefits
Compensation and benefits
- Base salary: USD 230,000 to 300,000 per year
- Equity
- Health, dental and vision coverage
- Retirement plan with company match
- Unlimited paid time off
- Relocation assistance
Location and work model
- San Mateo, California, United States
- Hybrid, 4 days per week in office
- Full-time
Benefits mentioned
- Compensation and benefits
- - Base salary: USD 230,000 to 300,000 per year
- - Equity
- - Health, dental and vision coverage
- - Retirement plan with company match
- - Unlimited paid time off
- - Relocation assistance
- Location and work model
- - San Mateo, California, United States
- - Hybrid, 4 days per week in office
- - Full-time
Requirements mentioned
- What we're looking for
- - 5+ years in a customer-facing technical role, such as solutions or implementation engineering.
- - Solid background in distributed systems, data platforms and self-hosted or hybrid infrastructure.
- - Deep working knowledge of the major cloud providers, including compute, storage, networking and identity management.
- - A track record of installing software inside large organizations' own infrastructure.
- - Practical experience training machine learning models and a firm understanding of the stages of model training.
- - Proficiency in Python and AWS, with the ability to troubleshoot and take part in technical discussions throughout a project.
- - Skill at turning vague customer needs into clear architecture.
- - Ownership of the complete customer lifecycle after a sale, including onboarding, optimization and creating processes and playbooks from zero.
- - Comfort working in a startup or other fast-changing, ambiguous setting.
- - A technical degree, ideally in computer science or equivalent.
- - Willingness to travel roughly 15% of the time.
- Bonus points
- - Familiarity with additional cloud platforms, self-hosted infrastructure or ML tooling.
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