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. Work directly with large organizations as a hands-on technical lead, guiding AI initiatives from early conversations through to live deployment. The role combines engineering, pre-sales consulting and stakeholder management, and passes field insights back to internal product teams.
What you'll do
- Run technical discovery sessions, scope proofs of concept, and carry out load testing and evaluations to confirm the right architecture and deployment setup for each customer.
- Build proofs of concept and production integrations hands-on inside customer environments, working within their infrastructure and security constraints.
- Advise customers on model selection, fine-tuning approaches and evaluation practices as they move from experimentation to production.
- Manage relationships across multiple stakeholders, identify internal champions and align the right people to move opportunities forward.
- Share recurring customer challenges and deployment patterns with product and engineering teams to inform the roadmap.
- Travel domestically to customer sites as needed.
Requirements
What we're looking for
- 3+ years of experience in a technical, customer-facing role.
- A track record of delivering working AI or ML software in a client's own live systems, with hands-on exposure to large language model serving and fine-tuning.
- Working knowledge of open-model serving tools and the trade-offs involved in inference, plus comfort in the terminal.
- Experience deploying and running infrastructure for open-model inference.
- Solid Python programming ability, along with experience running GPU workloads on a major cloud platform and familiarity with Kubernetes.
- Executive presence in enterprise settings, able to hold a technical deep-dive with an engineer and present architecture trade-offs to a senior executive on the same day.
- Experience carrying a pre-sales technical engagement from the first call through proof of concept scoping, evaluations and model recommendations.
- Background at an AI-focused startup, or at an enterprise software company building AI features.
- Experience working with a major cloud provider in an AI capacity.
- Willingness to travel domestically to customers.
Bonus points
- Experience navigating enterprise organizational dynamics end-to-end.
- Experience with preference-based or reinforcement fine-tuning workflows.
Benefits
Compensation and benefits
- Base salary: USD 176,000 to 224,000 per year
- Equity
- Performance-based variable compensation
- Comprehensive benefits package
Location and work model
- Remote (US)
- Full-time
Benefits mentioned
- Compensation and benefits
- - Base salary: USD 176,000 to 224,000 per year
- - Equity
- - Performance-based variable compensation
- - Comprehensive benefits package
- Location and work model
- - Remote (US)
- - Full-time
Requirements mentioned
- What we're looking for
- - 3+ years of experience in a technical, customer-facing role.
- - A track record of delivering working AI or ML software in a client's own live systems, with hands-on exposure to large language model serving and fine-tuning.
- - Working knowledge of open-model serving tools and the trade-offs involved in inference, plus comfort in the terminal.
- - Experience deploying and running infrastructure for open-model inference.
- - Solid Python programming ability, along with experience running GPU workloads on a major cloud platform and familiarity with Kubernetes.
- - Executive presence in enterprise settings, able to hold a technical deep-dive with an engineer and present architecture trade-offs to a senior executive on the same day.
- - Experience carrying a pre-sales technical engagement from the first call through proof of concept scoping, evaluations and model recommendations.
- - Background at an AI-focused startup, or at an enterprise software company building AI features.
- - Experience working with a major cloud provider in an AI capacity.
- - Willingness to travel domestically to customers.
- Bonus points
- - Experience navigating enterprise organizational dynamics end-to-end.
- - Experience with preference-based or reinforcement fine-tuning workflows.
No Mondays shows this listing as the employer published it. Check the details on the employer's site before you apply.