AI Strategist

About the role

Smartcat, a Series C company building an agentic AI platform for enterprises, is hiring its first AI Strategist. You will build custom AI workflows and agents from scratch for the company's largest strategic customers, turning ambiguous business problems into scalable, measurable solutions. You will work in a pod with a Strategic Account Executive, a Technical Account Manager and sometimes a Forward Deployed Engineer, and you do not need to be a software engineer.

Key responsibilities

• Partner with business leaders and technical teams at strategic customers to scope high-value AI use cases and agree on success metrics
• Identify where AI workflows can deliver ROI and build the business case with the account team
• Design, build and deploy custom AI solutions and agents, using vector databases, MCP and RAG, and combining semantic and keyword search
• Own customer engagements end to end, from ideation through delivery, and train and enable customer teams to adopt the solutions
• Act as the voice of the customer, surfacing insights that inform the product roadmap, and contribute playbooks, reusable patterns and case studies

Required profile

• Experience in a customer-facing AI, solutions, consulting or technical role, ideally in B2B SaaS or enterprise environments
• A track record of building AI-powered workflows, agents or automations that solved real business problems
• Ability to translate ambiguous business problems into practical, scalable AI solutions and to engage both technical stakeholders and senior executives
• Customer-centric mindset, change management and customer enablement experience; leading cross-functional initiatives is a plus
• Flexibility to travel for customer engagements

Required skills

• Hands-on experience with Python and AI coding tools such as Claude, Cursor or Cline
• Familiarity with vector databases, MCP, RAG and agent design
• SQL or data analysis is a plus
• Command line, basic Linux administration and cloud infrastructure (AWS/GCP)

Ramp

• By day 30: learn the platform and AI agent capabilities, meet the pod partners and get set up with the AI tooling
• By day 60: join customer conversations to scope use cases and build and test a first custom solution
• By day 90: own a customer engagement from scoping to delivery, run enablement and feed insights back to Product