Conversational AI Manager

Roles and Responsibilities:

People leadership & team development

Manage and coach engineers across levels (L1–L5), including onboarding, performance management, career development, and promotion readiness.

Build a high-trust feedback culture with strong engineering fundamentals (code review, testing, documentation, incident learning).

Recruit and hire across multiple levels; help scale the team responsibly.

Delivery & execution

Own delivery outcomes: planning, prioritization, scope control, and risk management across concurrent projects.

Collaborate with Product and stakeholders to translate requirements into clear technical plans and measurable milestones.

Establish and improve agile operating rhythms (sprint/kanban, roadmapping, retros, metrics). Enforce CI/CD workflows (both with and without repositories) Conversational AI platform leadership

Lead implementation and enhancement of solutions built on Cognigy and/or Amazon Lex + Amazon Q (chat/voice bots, routing, integrations, and knowledge-driven experiences).

Ensure best practices for conversational design implementation, NLU/LLM prompt/tooling hygiene, and safe fallbacks/hand-offs to live agents.

Improve bot quality through evaluation, testing strategies, monitoring, and iterative optimization.

Operational excellence & Cross-functional collaboration

Define and enforce standards for reliability, observability, and on-call readiness (SLOs, logging, dashboards, alerts).

Drive incident response and root-cause reviews; ensure learnings translate into durable engineering changes.

Work with security/compliance stakeholders for data handling, retention, and access controls when integrating customer data sources.