Conversational AI Engineering Manager

Accountabilities: Lead, manage, and coach engineers across multiple levels, supporting onboarding, performance management, career development, and promotion readiness. Build a high-trust engineering culture centered on effective feedback, code reviews, testing, documentation, and learning from incidents. Recruit and hire engineering talent across different levels while supporting responsible team growth. Own delivery outcomes across concurrent projects, including planning, prioritization, scope management, dependency coordination, and risk mitigation. Partner with Product, clients, and other stakeholders to translate business requirements into clear technical plans, milestones, and measurable outcomes. Lead client interactions and stakeholder management throughout project planning and delivery. Create and review business and technical documentation, including BRDs, PRDs, FRDs, SOWs, and NFRDs. Document AI solutions through use cases, workflows, integrations, and AI-specific product and business requirements. Establish and continuously improve agile operating practices, including sprint or Kanban workflows, roadmaps, retrospectives, and engineering metrics. Establish and enforce CI/CD workflows across development environments, including workflows with and without source-code repositories. Lead implementation and enhancement of conversational AI solutions using platforms such as Cognigy and/or Amazon Lex with Amazon Q. Oversee conversational AI capabilities including chat and voice bots, routing, integrations, and knowledge-driven experiences. Establish best practices for conversational design, NLU and LLM implementation, prompt and tooling hygiene, and safe fallback or live-agent handoff mechanisms. Improve bot quality through structured evaluation, testing strategies, monitoring, and continuous optimization. Define and enforce standards for reliability, observability, logging, dashboards, alerting, service-level objectives, and on-call readiness. Lead incident response and root-cause analysis while ensuring lessons learned result in sustainable engineering improvements. Collaborate with security and compliance stakeholders on customer data handling, retention, access controls, and related requirements. Requirements Proven experience in engineering management, technical leadership, or a similar software engineering leadership role. Demonstrated experience managing and developing engineers across multiple levels and building high-performing technical teams. Strong experience delivering conversational AI solutions, including chat and/or voice bots, routing, integrations, and knowledge-based experiences. Hands-on experience with platforms such as Cognigy, Amazon Lex, Amazon Q, or comparable conversational AI technologies. Strong understanding of conversational design, NLU, LLM prompting, AI tooling, evaluation methodologies, and safe fallback mechanisms. Experience translating business requirements into technical solutions, delivery plans, milestones, and measurable outcomes. Strong client-facing and stakeholder-management capabilities, with confidence communicating technical concepts to both technical and non-technical audiences. Experience creating and reviewing BRDs, PRDs, FRDs, SOWs, NFRDs, and AI-specific technical documentation. Strong understanding of agile delivery methodologies, including Scrum or Kanban, roadmapping, retrospectives, and engineering metrics. Experience establishing or enforcing CI/CD practices and modern software delivery workflows. Knowledge of software engineering fundamentals, including code review, automated testing, documentation, observability, and production reliability. Experience with incident management, root-cause analysis, SLOs, monitoring, logging, dashboards, and alerting. Ability to collaborate effectively with Product, Engineering, clients, security, compliance, and other cross-functional stakeholders. Strong organizational, problem-solving, communication, and decision-making skills. Ability to operate effectively in a remote, fast-paced, globally distributed environment. Benefits Fully remote working opportunity in India. Leadership role with significant influence over engineering teams, technical delivery, and conversational AI solutions. Opportunity to work with modern conversational AI, NLU, and LLM technologies. Exposure to global clients and cross-functional teams. Competitive compensation program. Medical, dental, and vision benefits. Opportunities for career advancement within a growing organization. Collaborative culture focused on professional development, continuous improvement, and employee growth. Opportunity to contribute to innovative AI solutions spanning chat, voice, automation, integrations, and knowledge-driven experiences.