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About the Role
Own the technical and operational success of customers from pre-sale through post-sale, including running POVs, leading onboarding, configuring AI workflows, and driving adoption and expansion outcomes. This role involves embedding with customers to make AI work in production by configuring integrations, managing agent performance, solving workflow problems, and proving value.
Responsibilities
- Partner with AEs to run high-impact POVs (proof-of-value pilots)
- Own technical validation: data mapping, light integrations, prompt setup, outcome measurement
- Be the technical face of the company in pre-sale cycles
- Own onboarding: configure AI workflows, connect integrations, ensure functional go-live
- Drive activation: monitor AI output quality, guide user enablement, tune prompts and logic
- Prove and communicate value: track impact metrics, partner with AE and Value team on expansions
- Retain ownership of technical success through renewals
Requirements
- AI-fluent: Understand how AI models work (prompting, edge cases, accuracy, drift) and can speak confidently about them with customers.
- Stay ahead of AI trends, experiment with the latest tools and techniques, and aren't afraid to hack together fast, creative solutions to demonstrate what’s possible.
- Know that delivering AI in the wild takes iteration, curiosity, and a builder’s mindset.
- Technical: Comfortable reading API docs, debugging JSON payloads, writing basic SQL, and working hands-on with data.
- Operational: Able to map a customer’s workflow, translate it into a system configuration, and drive the changes needed to make AI stick.
- Customer-facing: Able to lead a technical working session and hold the room in an executive QBR.
- Outcome-oriented: Deliver successful, referenceable deployments that grow.
Skills
- API integrations
- Reading API docs
- Testing endpoints
- Structuring payloads
- Debugging authentication or schema issues
- Workflow automation platforms
- GTM systems (e.g., Salesforce, Zendesk, Intercom, Atlassian, Gong)
- AI models
- Prompting
- Basic SQL
Experience Level
- 2–4 years in a solutions engineering, technical consulting, TAM, or implementation role at a SaaS, AI, automation, or consulting firm
About the Company
- Mosaic AI is the only enterprise AI platform built for technical support in highly configurable, multi-product companies.
- The platform unifies customer, product, and support context scattered across a company's systems, then acts on it across the case lifecycle: automating what we can, escalating to a human expert when it matters.
- Built on 100+ deep integrations, the platform runs products already live in production, including Self-Service, Knowledge, Triage, Assist, Intelligence, Alerting, and QA, all sharing one foundation so they ship fast and improve as the platform grows.
- This is an exciting, unusual place to build. Each product we launch would have been an entire company in the pre-AI era; for us, it's a focused product on common infrastructure, so each deployment builds on the last.
- The no-code Agent Builder lets teams design and deploy agents with governance and traceability, while the Customer Context Model routes recurring issues and account risk to the teams that can fix them.
- Every deployment lowers our customers' cost to serve.
- We're hiring engineers and product leaders who want to build systems that get more capable the more they run.