At a glance
- Employment
- Full-time
- Workplace
- Remote
- Location
- Remote
About Baseten
- Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
About the role
- The Solutions Architect will partner with Sales and customers to translate business needs into technical solutions, run technical discovery, and guide deployments.
- This role involves working across technical discovery, solution design, demos, and hands-on customer implementations.
- The position is ideal for entrepreneurial, customer-facing technical professionals interested in how modern companies adopt AI at scale.
Responsibilities
- Partner with Sales on customer discovery calls.
- Lead demos and technical scoping to align on success criteria, architecture, and deployment approach.
- Own benchmarking and repeatable deployments for various modalities including LLMs, embeddings, and image/video generation.
- Advise on infrastructure tradeoffs such as GPU selection and latency versus throughput optimization.
- Drive consistent playbook-style deployments for common models and use cases.
- Become a power user of runtimes such as vLLM, SGLang, and TRT-LLM.
- Scope POCs and keep stakeholders aligned on timelines, deliverables, and next steps.
- Act as the project manager for POCs.
- Coordinate with Forward Deployed Engineering (FDE) for complex technical work.
Requirements
- AI/ML background with the ability to credibly discuss topics with technical stakeholders.
- Strong customer-facing communication skills.
- Ability to run structured discovery and clarify ambiguous requirements.
- Technical depth to scope solutions without needing to write production code.
- Ability to script and prototype as needed, including comfort with rapid technical workflows.
Preferred qualifications
- Experience running or supporting benchmarks for ML inference deployments.
- Familiarity with infrastructure tradeoffs relevant to inference performance and cost.
- Experience serving as a cross-functional technical lead for customer POCs.
Benefits
- Competitive compensation
- Meaningful equity
- Flexible PTO policy
- Company-wide Winter Break
- Paid parental leave
- Fertility and family-building stipend through Carrot
- Exposure to a variety of ML startups
Workplace
- Remote
Skills
- AI
- ML
- LLMs
- vLLM
- SGLang
- TRT-LLM
- GPU
- Inference
