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Salary: USD 150,000 - 200,000 / annual
Cresta is an AI platform that combines conversational AI agents, real-time human agent augmentation, and conversation intelligence to drive revenue and efficiency across customer experience channels. Founded from Stanford AI Lab and backed by a16z, Greylock, and Sequoia, Cresta serves leading companies including United Airlines, Cox Communications, and Marriott.
As an AI Strategist, you will be the embedded AI leader for Cresta customers, connecting customer conversations and business needs with Cresta's AI capabilities to create prioritized plans and measurable results. You will identify where automation and augmentation deliver the most value, build roadmaps, and ensure work ships and delivers impact.
You will not build AI agents from scratch—Forward Deployed Engineers and Product Managers handle that. Instead, you focus on optimizing deployed AI, finding next opportunities, piloting new capabilities, and proving business impact. You will be analytical, commercially minded, and credible with senior stakeholders across CX, Operations, Product, Sales, and IT. You are technical enough to work closely with engineering teams and provide tight feedback loops to product and engineering.
Key responsibilities include:
**AI Strategy and Roadmap:** Identify automation and augmentation opportunities across contact centers and customer experience operations. Prioritize initiatives by expected ROI and build business cases. Build and maintain enterprise AI roadmaps that stay current as priorities and capabilities evolve. Align stakeholders across functions on priorities, sequencing, and success criteria.
**Conversation Intelligence and Business Insights:** Use conversation data to surface customer friction and emerging trends. Identify operational inefficiencies and recommend changes. Share Voice of Customer insights with customer leadership and Cresta product teams. Measure and report business impact in terms executives care about: containment, handle time, conversion, CSAT, and cost to serve.
**AI Innovation and Execution:** Stay current on new Cresta features and bring relevant ones to customers early. Pilot emerging AI capabilities, define success criteria, and decide whether to scale. Optimize live AI agents by analyzing performance, reviewing conversations, and recommending changes to prompts, workflows, and configurations. Coordinate deployments with Forward Deployed Engineers and Product Managers. Measure realized value after launch against original business cases.
**Requirements:**
- 5+ years in technology consulting, strategy, product, analytics, implementation, or customer success roles, ideally with AI or LLM-first products
- Track record of building roadmaps, prioritizing by ROI, and writing business cases that senior stakeholders approve
- Strong data skills; comfortable analyzing conversation or operational data, designing experiments (A/B tests), and monitoring performance
- Working knowledge of how LLM-based AI agents function, including prompts, tools/function calling, and retrieval-augmented generation. Hands-on experience with an agent project (even personal) is a plus. Can read and reason about system behavior and discuss tradeoffs with engineers, but production coding not required
- Experience leading cross-functional work and influencing senior customer stakeholders across CX, Operations, Product, Sales, and IT
- Excellent written, verbal, and presentation skills; can explain complex findings to executives in plain language
- Strong project management skills and bias for action; turn ambiguity into plans and follow through to results
- Curious, self-driven, comfortable learning quickly in fast-moving startup environment; passionate about AI, automation, and customer experience
- Bachelor's degree in Business, Computer Science, Engineering, or related field, or equivalent experience
**Bonus:** Familiarity with customer support and contact center operations (AHT, FCR, containment, QA); experience with conversation intelligence, speech analytics, or voice-of-customer programs; background in management consulting, product management, or forward deployed roles; startup or high-growth SaaS experience; comfort with SQL or BI tools for self-serve analysis.
