Why This Job is Featured on The SaaS Jobs
This Solution Engineer role sits at a common pressure point in modern SaaS: turning advanced platform capabilities into outcomes customers can validate and adopt. With Fastino focused on small language models delivered via models and APIs, the work is closely tied to how AI-native SaaS products are evaluated, integrated, and operationalised, especially during pre-sales and early production stages.
For a SaaS career, the position builds durable experience in technical value articulation, solution design, and customer-facing discovery, all in environments where product maturity and go-to-market learning happen in parallel. The mix of demos, architecture guidance, fine-tuning and deployment support, and documentation creation develops a toolkit that transfers across developer platforms, data and AI products, and infrastructure-led SaaS. It also creates a direct feedback loop into product and engineering through recurring patterns surfaced across accounts.
This role is best suited to someone who enjoys working across functions and can switch between hands-on technical work and stakeholder communication without losing precision. It will fit professionals who like ambiguity at the edge of product definition, and who prefer being measured by customer adoption signals and clarity of technical guidance rather than purely internal delivery.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Solution Engineer – Small Language Models
Full-time | Hybrid- Palo Alto | Reports to Founders
Introduction
- Join us at Fastino as we build the next generation of LLMs. Our team, boasting alumni from Google Research, Apple, Stanford, and Cambridge, is on a mission to develop specialized, efficient AI.
- Fastino’s GLiNER family of open-source models has been downloaded more than 5 million times and is used by companies such as NVIDIA, Meta, and Airbnb.
- Fastino has raised $25M (as featured in TechCrunch) through our seed round and is backed by leading investors including Microsoft, Khosla Ventures, Insight Partners, GitHub CEO Thomas Dohmke, Docker CEO Scott Johnston, and others.
What You’ll Work On
- Partner closely with Fastino’s customers to ensure they achieve real business value from our models.
- Operate at the intersection of engineering, sales, and language model research, helping customers adopt Fastino’s technology and build production-ready AI systems.
- Partner with senior technical and business stakeholders to understand pre-sales and early adoption needs, guide customers on AI and agentic system design, and identify high-impact use cases.
- Collaborate with customer engineering teams and internal stakeholders to demonstrate the value of Fastino’s solutions, recommend architectural patterns, and help kickstart implementation using our models and APIs.
- Lead technical demos, scope customer use cases, recommend system architectures, and provide hands-on advisory support around model fine-tuning, deployment, and evaluation.
- Create and maintain documentation, guides, and FAQs based on common customer questions surfaced during pre-sales and onboarding.
- Develop and nurture strong customer relationships throughout evaluation, validation, and purchasing, serving as a trusted technical partner as customers move into production.
- Foster customer advocacy and represent the voice of the customer internally by gathering feedback, identifying patterns across accounts, and collaborating with product and engineering teams to inform roadmap and feature prioritization.
- Serve as the first line of defense for security, privacy, and compliance questions by explaining Fastino’s standardized materials, guiding customers to relevant documentation, and escalating complex requirements to internal teams as needed.
What We’re Looking For
- 5+ years of experience in a technical pre-sales, solution engineering, or similar role, supporting senior technical and business stakeholders at complex organizations.
- Foundational training and hands-on experience with programming languages such as Python or JavaScript.
- Experience delivering prototypes of Generative AI or traditional ML solutions, with working knowledge of cloud and network architectures.
- Strong presentation and communication skills, with the ability to translate complex technical concepts to both technical and non-technical audiences, including senior leaders.
- Ownership mindset with the ability to take problems end-to-end and quickly ramp on new technologies as needed.
- Humble, collaborative, and customer-oriented attitude with a strong desire to help teammates and customers succeed.
