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Sona is an AI-native workforce management platform for frontline organisations (restaurants, hospitals, schools, airlines, etc.), serving a $500bn+ market. The company has raised over $100M and operates across the UK, US, and Europe with 100+ enterprise customers.
The Director of Support and Services will build and scale an AI-first support function, combining agent architecture, operational design, product collaboration, and team leadership. This is a hands-on leadership role focused on solving support at scale without proportional headcount growth.
Key responsibilities include:
- Design and own the agentic support operating model end-to-end, defining what problems agents solve, escalation thresholds, and human review triggers. Own the configuration layer to evolve agent behaviour without code changes.
- Architect multi-tier agent routing and escalation logic, matching assignments to customer segments (self-service, assisted, premium, white-glove) to maximize agent resolution while maintaining quality.
- Own the cost model for agent operation, human supervision overhead, and escalation decisions. Use agent data to determine when to invest in agent capability versus escalating to humans.
- Establish and own agent quality and capability metrics (resolution rates, accuracy, customer satisfaction, human exception workload). Run retrospectives on agent failures to identify systemic improvements.
- Collaborate closely with Product and ML teams to improve agent behaviour, identify friction points, and make the business case for training agents, escalating, or fixing the product.
- Direct a dedicated engineering resource to build agent infrastructure, including orchestration logic, intelligent routing, multi-turn resolution agents, and predictive issue detection.
- Build and lead a lean orchestration team focused on agent configuration, quality monitoring, exception handling, and continuous improvement—emphasizing systemic improvement over individual heroics.
- Define tiered support and services models based on customer segment and agent capability, with white-glove or premium services where human expertise differentiates.
Success is measured by agentic metrics: resolution rates, accuracy, cost per resolution, and human time saved. The goal is support infrastructure where agents are the production layer and humans orchestrate them.
Requirements:
- 7+ years in customer support, customer success, or operations roles, including at least 2 years in a leadership capacity. Must have operated at scale and understand support economics.
- Hands-on experience building or scaling AI-first workflows where AI is the production layer. Must have defined what an AI system should do, found failure modes, and iterated on behaviour—not just evaluated vendor solutions.
- Deep familiarity with agentic systems and LLM behaviour. Must understand agent limitations, failure modes, hallucination risks, and how to structure problems for agent success. Ability to read traces, identify where agents fail, and communicate fixes to engineers.
- Track record of solving problems systematically through configuration and process design, not headcount scaling. Experience building tiered models, designing escalation logic, and multiplying team impact without adding headcount.
- Ability to reason about trade-offs in agent design, understanding the tension between agent autonomy (speed, scale) and human oversight (quality, safety), and making commercial cases for design decisions.
- Comfortable identifying friction and building solutions. Moves in ambiguity and iterates rapidly.
- Bonus: SaaS experience, background in product/engineering/data, experience building observability or quality frameworks for AI/ML systems, large-scale customer operations or contact centre modernisation experience, or prior experience with agent orchestration platforms.
